Tools: The $255M Wake-Up Call: How Cryptographic Audit Trails Could Have Caught a Quant Fund Fraud in Minutes, Not Years

Table of Contents ## 1. The Two Sigma Incident: What Actually Happened ## The Setup ## The Vulnerability ## The Exploit ## The Timeline of Failure ## The Damage ## 2. Why Traditional Logs Failed ## Problem 1: No Tamper Evidence ## Problem 2: No Completeness Guarantees ## Problem 3: Single-Party Control ## Problem 4: Trust-Based Verification ## 3. VCP v1.1: The Three-Layer Architecture ## 4. Layer 1: Event Integrity with Hash Chains ## The Concept ## Implementation ## Application to Two Sigma ## 5. Layer 2: Collection Integrity with Merkle Trees ## The Problem with Hash Chains Alone ## Enter Merkle Trees ## The Completeness Property ## Implementation ## Application to Two Sigma ## 6. Layer 3: External Verifiability with Anchoring ## The Trust Problem ## The Solution: External Anchoring ## Implementation ## Application to Two Sigma ## 7. VCP-GOV: Cryptographic Model Governance ## ModelHash: The Cryptographic Fingerprint ## Correlation Anomaly Detection ## 8. Multi-Log Replication: Defeating Omission Attacks ## The Attack Vector ## VCP v1.1's Solution ## Gossip Protocol ## 9. Code Examples: Building a VCP Event Stream ## Complete Working Example ## 10. Regulatory Compliance ## MiFID II RTS 25 (EU) ## EU AI Act Article 12 ## SEC Rule 17a-4 ## SEC AI Task Force (August 2025) ## 11. Performance Benchmarks ## 12. Getting Started with VCP ## Quick Start ## Resources ## Compliance Tiers ## Conclusion ## About the Author In September 2025, federal prosecutors charged a former Two Sigma quant researcher with manipulating 14 live trading models over nearly two years. The manipulation went undetected despite the firm knowing about the vulnerability since 2019. Total damage: $165 million in client losses, $90 million in fines, and criminal charges carrying up to 60 years. The kicker? This wasn't a sophisticated zero-day exploit. It was a database with overly permissive access controls. A problem any junior security engineer could have flagged. This article breaks down exactly what went wrong, and how VeritasChain Protocol (VCP) v1.1—an open cryptographic audit standard—would have detected the fraud within minutes using hash chains, Merkle trees, and external anchoring. No trust required. Just math. Two Sigma is a $60B+ quantitative hedge fund. Their edge: sophisticated algorithmic models that analyze data and generate trading signals. Each model is supposed to be decorrelated—providing unique, independent predictions that contribute distinct alpha to the portfolio. To enforce decorrelation, models have mathematical parameters that prevent them from copying each other's predictions. Two Sigma had a formal approval process for model changes. Model code lived in secure "Jar" files that only engineering could modify. But as model parameters grew larger, researchers started storing them in a secondary database called celFS. Here's the problem: celFS had no access controls. Multiple employees had unrestricted read-write access. Jian Wu, a senior quant researcher, figured this out. He directly modified the "decorrelation parameters" in celFS, reducing them to near-zero. This made his models essentially copy the predictions of existing successful models instead of generating independent forecasts. Result: His models looked like they were generating high alpha. In reality, they were just riding the coattails of other models. Four years from initial warning to comprehensive fix. Nearly two years of active manipulation before detection. Two Sigma presumably had logging. They're a sophisticated shop. So why didn't they catch this? Standard database logs have no cryptographic proof that entries haven't been altered. If Wu had wanted to delete log entries documenting his parameter changes, there would have been no mathematical proof of tampering. Traditional logs can't prove that all relevant events were recorded. An insider could selectively delete records, and auditors would have no way to detect the omission. The audit trail existed only within Two Sigma's systems. There was no external reference point to verify accuracy. Auditors had to trust that Two Sigma's logs were accurate. In a fraud investigation, trusting the potentially fraudulent party is... suboptimal. VeritasChain Protocol (VCP) v1.1 is designed around one principle: "Verify, Don't Trust" Third-party auditors can verify audit trail integrity without trusting the log generator. Here's how: Each layer builds on the one below, providing increasingly strong guarantees. Every trading event gets a SHA-256 hash. Each hash includes the previous hash, creating a chain: Key property: Modifying any historical event invalidates all subsequent hashes. Without VCP, the modification was invisible in the database. Hash chains detect modifications to existing events. But what if an attacker simply never records an incriminating event? The hash chain would be valid—just incomplete. A Merkle Tree is a binary tree where: If you omit Event C, the Merkle Root changes. There's no way to produce the same root without including all original events. Scenario: Wu modifies a parameter and tries to delete the log entry. Layers 1 and 2 are powerful, but there's still a gap: all proofs are generated by the entity being audited. A sophisticated attacker could: VCP requires Merkle Roots to be anchored to external, immutable systems: Once anchored, the Merkle Root is fixed. Any attempt to present different data fails verification. Scenario: Wu manipulates parameters from 2021-2023. In late 2023, manipulation is discovered. Wu tries to alter historical records. The Two Sigma case had a specific failure mode: model parameters could change without cryptographic verification. VCP-GOV addresses this with the ModelHash field. The CorrelationAnomaly flag in VCP-GOV is specifically relevant to Two Sigma's case: Wu's manipulation specifically caused his models to correlate with existing models. This flag would have caught it. What if an attacker controls the log server? They could simply not record incriminating events. Events must be sent to multiple independent log servers simultaneously: Log servers exchange signed Merkle Roots to detect discrepancies: Here's a complete example showing VCP in action for a trading system: Timestamp precision requirements: Requires high-risk AI systems to maintain tamper-evident automatic logging. 2022 amendments allow audit trail alternative to WORM storage: VCP satisfies both through Merkle Proofs. Measured on commodity hardware (AWS c5.xlarge): VCP adds < 1ms latency to the critical path and can handle even HFT workloads. The Two Sigma incident wasn't a sophisticated attack. It was a database with bad access controls and a process that "involved no real review." $255 million in damages ($165M client losses + $90M fines) from a problem any security engineer could have flagged. VCP v1.1 provides cryptographic guarantees that make such manipulation immediately detectable: The technology exists. The specification is open. The implementation is straightforward. The question isn't whether cryptographic audit trails will become standard—it's whether your firm will adopt them before the next incident or after. This article was produced by the VeritasChain Standards Organization (VSO), a non-profit, vendor-neutral standards body developing open cryptographic audit standards for AI-driven systems. VSO operates under one principle: "Verify, Don't Trust." Have questions or want to contribute? Open an issue on GitHub or reach out at [email protected]. Tags: #cryptography #fintech #security #opensource #blockchain #audit #trading #compliance #ai Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse CODE_BLOCK: March 2019 → Employee warns management about celFS vulnerability January 2022 → Senior engineer reiterates access control risks May 2022 → Accidental parameter overwrite demonstrates the risk June 2022 → Partial, inadequate restrictions implemented August 2023 → Comprehensive monitoring finally deployed August 2023 → Wu's manipulation detected, he's terminated September 2025 → Criminal charges filed Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: March 2019 → Employee warns management about celFS vulnerability January 2022 → Senior engineer reiterates access control risks May 2022 → Accidental parameter overwrite demonstrates the risk June 2022 → Partial, inadequate restrictions implemented August 2023 → Comprehensive monitoring finally deployed August 2023 → Wu's manipulation detected, he's terminated September 2025 → Criminal charges filed CODE_BLOCK: March 2019 → Employee warns management about celFS vulnerability January 2022 → Senior engineer reiterates access control risks May 2022 → Accidental parameter overwrite demonstrates the risk June 2022 → Partial, inadequate restrictions implemented August 2023 → Comprehensive monitoring finally deployed August 2023 → Wu's manipulation detected, he's terminated September 2025 → Criminal charges filed CODE_BLOCK: ┌─────────────────────────────────────────────────────────────────┐ │ LAYER 3: EXTERNAL VERIFIABILITY │ │ Anchor Merkle Roots to blockchain/TSA │ │ → Third parties verify without trusting log generator │ ├─────────────────────────────────────────────────────────────────┤ │ LAYER 2: COLLECTION INTEGRITY │ │ RFC 6962 Merkle Trees │ │ → Detect if ANY event was omitted from the log │ ├─────────────────────────────────────────────────────────────────┤ │ LAYER 1: EVENT INTEGRITY │ │ SHA-256 hash chains + Ed25519 signatures │ │ → Detect if ANY event was modified after recording │ └─────────────────────────────────────────────────────────────────┘ Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: ┌─────────────────────────────────────────────────────────────────┐ │ LAYER 3: EXTERNAL VERIFIABILITY │ │ Anchor Merkle Roots to blockchain/TSA │ │ → Third parties verify without trusting log generator │ ├─────────────────────────────────────────────────────────────────┤ │ LAYER 2: COLLECTION INTEGRITY │ │ RFC 6962 Merkle Trees │ │ → Detect if ANY event was omitted from the log │ ├─────────────────────────────────────────────────────────────────┤ │ LAYER 1: EVENT INTEGRITY │ │ SHA-256 hash chains + Ed25519 signatures │ │ → Detect if ANY event was modified after recording │ └─────────────────────────────────────────────────────────────────┘ CODE_BLOCK: ┌─────────────────────────────────────────────────────────────────┐ │ LAYER 3: EXTERNAL VERIFIABILITY │ │ Anchor Merkle Roots to blockchain/TSA │ │ → Third parties verify without trusting log generator │ ├─────────────────────────────────────────────────────────────────┤ │ LAYER 2: COLLECTION INTEGRITY │ │ RFC 6962 Merkle Trees │ │ → Detect if ANY event was omitted from the log │ ├─────────────────────────────────────────────────────────────────┤ │ LAYER 1: EVENT INTEGRITY │ │ SHA-256 hash chains + Ed25519 signatures │ │ → Detect if ANY event was modified after recording │ └─────────────────────────────────────────────────────────────────┘ CODE_BLOCK: h₀ = SHA-256(event₀) h₁ = SHA-256(h₀ || event₁) h₂ = SHA-256(h₁ || event₂) ... hₙ = SHA-256(hₙ₋₁ || eventₙ) Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: h₀ = SHA-256(event₀) h₁ = SHA-256(h₀ || event₁) h₂ = SHA-256(h₁ || event₂) ... hₙ = SHA-256(hₙ₋₁ || eventₙ) CODE_BLOCK: h₀ = SHA-256(event₀) h₁ = SHA-256(h₀ || event₁) h₂ = SHA-256(h₁ || event₂) ... hₙ = SHA-256(hₙ₋₁ || eventₙ) COMMAND_BLOCK: import hashlib import json from dataclasses import dataclass, asdict from typing import Optional @dataclass class VCPEvent: event_id: str event_type: str # SIG, ORD, ACK, EXE, REJ timestamp_ns: int symbol: str price: float quantity: float side: str algo_id: str model_hash: str prev_hash: Optional[str] = None event_hash: Optional[str] = None def compute_hash(self) -> str: """Compute SHA-256 hash using RFC 8785 canonical JSON""" # Create canonical representation (sorted keys, no whitespace) canonical = json.dumps( {k: v for k, v in asdict(self).items() if k not in ['event_hash']}, sort_keys=True, separators=(',', ':') ) return hashlib.sha256(canonical.encode()).hexdigest() class VCPEventChain: def __init__(self): self.events: list[VCPEvent] = [] self.latest_hash: Optional[str] = None def append(self, event: VCPEvent) -> VCPEvent: """Add event to chain with hash linking""" event.prev_hash = self.latest_hash event.event_hash = event.compute_hash() self.latest_hash = event.event_hash self.events.append(event) return event def verify_chain(self) -> bool: """Verify entire chain integrity""" prev_hash = None for event in self.events: if event.prev_hash != prev_hash: return False if event.event_hash != event.compute_hash(): return False prev_hash = event.event_hash return True Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: import hashlib import json from dataclasses import dataclass, asdict from typing import Optional @dataclass class VCPEvent: event_id: str event_type: str # SIG, ORD, ACK, EXE, REJ timestamp_ns: int symbol: str price: float quantity: float side: str algo_id: str model_hash: str prev_hash: Optional[str] = None event_hash: Optional[str] = None def compute_hash(self) -> str: """Compute SHA-256 hash using RFC 8785 canonical JSON""" # Create canonical representation (sorted keys, no whitespace) canonical = json.dumps( {k: v for k, v in asdict(self).items() if k not in ['event_hash']}, sort_keys=True, separators=(',', ':') ) return hashlib.sha256(canonical.encode()).hexdigest() class VCPEventChain: def __init__(self): self.events: list[VCPEvent] = [] self.latest_hash: Optional[str] = None def append(self, event: VCPEvent) -> VCPEvent: """Add event to chain with hash linking""" event.prev_hash = self.latest_hash event.event_hash = event.compute_hash() self.latest_hash = event.event_hash self.events.append(event) return event def verify_chain(self) -> bool: """Verify entire chain integrity""" prev_hash = None for event in self.events: if event.prev_hash != prev_hash: return False if event.event_hash != event.compute_hash(): return False prev_hash = event.event_hash return True COMMAND_BLOCK: import hashlib import json from dataclasses import dataclass, asdict from typing import Optional @dataclass class VCPEvent: event_id: str event_type: str # SIG, ORD, ACK, EXE, REJ timestamp_ns: int symbol: str price: float quantity: float side: str algo_id: str model_hash: str prev_hash: Optional[str] = None event_hash: Optional[str] = None def compute_hash(self) -> str: """Compute SHA-256 hash using RFC 8785 canonical JSON""" # Create canonical representation (sorted keys, no whitespace) canonical = json.dumps( {k: v for k, v in asdict(self).items() if k not in ['event_hash']}, sort_keys=True, separators=(',', ':') ) return hashlib.sha256(canonical.encode()).hexdigest() class VCPEventChain: def __init__(self): self.events: list[VCPEvent] = [] self.latest_hash: Optional[str] = None def append(self, event: VCPEvent) -> VCPEvent: """Add event to chain with hash linking""" event.prev_hash = self.latest_hash event.event_hash = event.compute_hash() self.latest_hash = event.event_hash self.events.append(event) return event def verify_chain(self) -> bool: """Verify entire chain integrity""" prev_hash = None for event in self.events: if event.prev_hash != prev_hash: return False if event.event_hash != event.compute_hash(): return False prev_hash = event.event_hash return True CODE_BLOCK: Merkle Root / \ H(AB) H(CD) / \ / \ H(A) H(B) H(C) H(D) | | | | Event Event Event Event A B C D Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: Merkle Root / \ H(AB) H(CD) / \ / \ H(A) H(B) H(C) H(D) | | | | Event Event Event Event A B C D CODE_BLOCK: Merkle Root / \ H(AB) H(CD) / \ / \ H(A) H(B) H(C) H(D) | | | | Event Event Event Event A B C D COMMAND_BLOCK: import hashlib from typing import List, Tuple, Optional class MerkleTree: """RFC 6962 compliant Merkle Tree implementation""" LEAF_PREFIX = b'\x00' NODE_PREFIX = b'\x01' def __init__(self, event_hashes: List[str]): self.leaves = [bytes.fromhex(h) for h in event_hashes] self.tree = self._build_tree() def _hash_leaf(self, data: bytes) -> bytes: """Hash a leaf node: SHA-256(0x00 || data)""" return hashlib.sha256(self.LEAF_PREFIX + data).digest() def _hash_node(self, left: bytes, right: bytes) -> bytes: """Hash an internal node: SHA-256(0x01 || left || right)""" return hashlib.sha256(self.NODE_PREFIX + left + right).digest() def _build_tree(self) -> List[List[bytes]]: """Build complete Merkle tree""" if not self.leaves: return [[hashlib.sha256(b'').digest()]] # Hash leaves current_level = [self._hash_leaf(leaf) for leaf in self.leaves] tree = [current_level] # Build tree bottom-up while len(current_level) > 1: next_level = [] for i in range(0, len(current_level), 2): left = current_level[i] right = current_level[i + 1] if i + 1 < len(current_level) else left next_level.append(self._hash_node(left, right)) current_level = next_level tree.append(current_level) return tree @property def root(self) -> str: """Get Merkle root as hex string""" return self.tree[-1][0].hex() def get_proof(self, index: int) -> List[Tuple[str, str]]: """ Generate Merkle proof for leaf at index. Returns list of (hash, position) tuples. """ if index >= len(self.leaves): raise IndexError("Leaf index out of range") proof = [] for level in self.tree[:-1]: sibling_index = index ^ 1 # XOR to get sibling if sibling_index < len(level): position = 'right' if index % 2 == 0 else 'left' proof.append((level[sibling_index].hex(), position)) index //= 2 return proof @staticmethod def verify_proof( leaf_hash: str, proof: List[Tuple[str, str]], root: str ) -> bool: """Verify a Merkle proof""" current = hashlib.sha256( MerkleTree.LEAF_PREFIX + bytes.fromhex(leaf_hash) ).digest() for sibling_hash, position in proof: sibling = bytes.fromhex(sibling_hash) if position == 'right': current = hashlib.sha256( MerkleTree.NODE_PREFIX + current + sibling ).digest() else: current = hashlib.sha256( MerkleTree.NODE_PREFIX + sibling + current ).digest() return current.hex() == root # Usage example events = ['event1_hash', 'event2_hash', 'event3_hash', 'event4_hash'] tree = MerkleTree(events) print(f"Merkle Root: {tree.root}") # Generate proof for event at index 2 proof = tree.get_proof(2) print(f"Proof for event 2: {proof}") # Verify the proof is_valid = MerkleTree.verify_proof(events[2], proof, tree.root) print(f"Proof valid: {is_valid}") Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: import hashlib from typing import List, Tuple, Optional class MerkleTree: """RFC 6962 compliant Merkle Tree implementation""" LEAF_PREFIX = b'\x00' NODE_PREFIX = b'\x01' def __init__(self, event_hashes: List[str]): self.leaves = [bytes.fromhex(h) for h in event_hashes] self.tree = self._build_tree() def _hash_leaf(self, data: bytes) -> bytes: """Hash a leaf node: SHA-256(0x00 || data)""" return hashlib.sha256(self.LEAF_PREFIX + data).digest() def _hash_node(self, left: bytes, right: bytes) -> bytes: """Hash an internal node: SHA-256(0x01 || left || right)""" return hashlib.sha256(self.NODE_PREFIX + left + right).digest() def _build_tree(self) -> List[List[bytes]]: """Build complete Merkle tree""" if not self.leaves: return [[hashlib.sha256(b'').digest()]] # Hash leaves current_level = [self._hash_leaf(leaf) for leaf in self.leaves] tree = [current_level] # Build tree bottom-up while len(current_level) > 1: next_level = [] for i in range(0, len(current_level), 2): left = current_level[i] right = current_level[i + 1] if i + 1 < len(current_level) else left next_level.append(self._hash_node(left, right)) current_level = next_level tree.append(current_level) return tree @property def root(self) -> str: """Get Merkle root as hex string""" return self.tree[-1][0].hex() def get_proof(self, index: int) -> List[Tuple[str, str]]: """ Generate Merkle proof for leaf at index. Returns list of (hash, position) tuples. """ if index >= len(self.leaves): raise IndexError("Leaf index out of range") proof = [] for level in self.tree[:-1]: sibling_index = index ^ 1 # XOR to get sibling if sibling_index < len(level): position = 'right' if index % 2 == 0 else 'left' proof.append((level[sibling_index].hex(), position)) index //= 2 return proof @staticmethod def verify_proof( leaf_hash: str, proof: List[Tuple[str, str]], root: str ) -> bool: """Verify a Merkle proof""" current = hashlib.sha256( MerkleTree.LEAF_PREFIX + bytes.fromhex(leaf_hash) ).digest() for sibling_hash, position in proof: sibling = bytes.fromhex(sibling_hash) if position == 'right': current = hashlib.sha256( MerkleTree.NODE_PREFIX + current + sibling ).digest() else: current = hashlib.sha256( MerkleTree.NODE_PREFIX + sibling + current ).digest() return current.hex() == root # Usage example events = ['event1_hash', 'event2_hash', 'event3_hash', 'event4_hash'] tree = MerkleTree(events) print(f"Merkle Root: {tree.root}") # Generate proof for event at index 2 proof = tree.get_proof(2) print(f"Proof for event 2: {proof}") # Verify the proof is_valid = MerkleTree.verify_proof(events[2], proof, tree.root) print(f"Proof valid: {is_valid}") COMMAND_BLOCK: import hashlib from typing import List, Tuple, Optional class MerkleTree: """RFC 6962 compliant Merkle Tree implementation""" LEAF_PREFIX = b'\x00' NODE_PREFIX = b'\x01' def __init__(self, event_hashes: List[str]): self.leaves = [bytes.fromhex(h) for h in event_hashes] self.tree = self._build_tree() def _hash_leaf(self, data: bytes) -> bytes: """Hash a leaf node: SHA-256(0x00 || data)""" return hashlib.sha256(self.LEAF_PREFIX + data).digest() def _hash_node(self, left: bytes, right: bytes) -> bytes: """Hash an internal node: SHA-256(0x01 || left || right)""" return hashlib.sha256(self.NODE_PREFIX + left + right).digest() def _build_tree(self) -> List[List[bytes]]: """Build complete Merkle tree""" if not self.leaves: return [[hashlib.sha256(b'').digest()]] # Hash leaves current_level = [self._hash_leaf(leaf) for leaf in self.leaves] tree = [current_level] # Build tree bottom-up while len(current_level) > 1: next_level = [] for i in range(0, len(current_level), 2): left = current_level[i] right = current_level[i + 1] if i + 1 < len(current_level) else left next_level.append(self._hash_node(left, right)) current_level = next_level tree.append(current_level) return tree @property def root(self) -> str: """Get Merkle root as hex string""" return self.tree[-1][0].hex() def get_proof(self, index: int) -> List[Tuple[str, str]]: """ Generate Merkle proof for leaf at index. Returns list of (hash, position) tuples. """ if index >= len(self.leaves): raise IndexError("Leaf index out of range") proof = [] for level in self.tree[:-1]: sibling_index = index ^ 1 # XOR to get sibling if sibling_index < len(level): position = 'right' if index % 2 == 0 else 'left' proof.append((level[sibling_index].hex(), position)) index //= 2 return proof @staticmethod def verify_proof( leaf_hash: str, proof: List[Tuple[str, str]], root: str ) -> bool: """Verify a Merkle proof""" current = hashlib.sha256( MerkleTree.LEAF_PREFIX + bytes.fromhex(leaf_hash) ).digest() for sibling_hash, position in proof: sibling = bytes.fromhex(sibling_hash) if position == 'right': current = hashlib.sha256( MerkleTree.NODE_PREFIX + current + sibling ).digest() else: current = hashlib.sha256( MerkleTree.NODE_PREFIX + sibling + current ).digest() return current.hex() == root # Usage example events = ['event1_hash', 'event2_hash', 'event3_hash', 'event4_hash'] tree = MerkleTree(events) print(f"Merkle Root: {tree.root}") # Generate proof for event at index 2 proof = tree.get_proof(2) print(f"Proof for event 2: {proof}") # Verify the proof is_valid = MerkleTree.verify_proof(events[2], proof, tree.root) print(f"Proof valid: {is_valid}") COMMAND_BLOCK: import requests import time from dataclasses import dataclass from typing import Optional from enum import Enum class AnchorTarget(Enum): BITCOIN = "bitcoin" OPENTIMESTAMPS = "opentimestamps" TSA = "tsa" @dataclass class AnchorRecord: merkle_root: str anchor_target: AnchorTarget anchor_timestamp: int anchor_proof: str # Transaction ID or TSA response class ExternalAnchor: """External anchoring for VCP Merkle Roots""" def __init__(self, target: AnchorTarget = AnchorTarget.OPENTIMESTAMPS): self.target = target def anchor(self, merkle_root: str) -> AnchorRecord: """Anchor a Merkle Root to external system""" if self.target == AnchorTarget.OPENTIMESTAMPS: return self._anchor_opentimestamps(merkle_root) elif self.target == AnchorTarget.TSA: return self._anchor_tsa(merkle_root) else: raise NotImplementedError(f"Anchor target {self.target} not implemented") def _anchor_opentimestamps(self, merkle_root: str) -> AnchorRecord: """ Anchor using OpenTimestamps (free, batched Bitcoin anchoring) Note: In production, use the official opentimestamps-client """ # This is a simplified example # Real implementation would use: pip install opentimestamps-client ots_url = "https://a.pool.opentimestamps.org/digest" response = requests.post( ots_url, data=bytes.fromhex(merkle_root), headers={'Content-Type': 'application/x-www-form-urlencoded'} ) if response.status_code == 200: return AnchorRecord( merkle_root=merkle_root, anchor_target=AnchorTarget.OPENTIMESTAMPS, anchor_timestamp=int(time.time()), anchor_proof=response.content.hex() ) else: raise Exception(f"OTS anchoring failed: {response.status_code}") def _anchor_tsa(self, merkle_root: str) -> AnchorRecord: """ Anchor using RFC 3161 Time Stamping Authority """ # RFC 3161 TSA request # In production, use a proper ASN.1 library tsa_url = "http://timestamp.digicert.com" # ... TSA implementation details ... raise NotImplementedError("TSA implementation requires ASN.1 library") def verify(self, record: AnchorRecord) -> bool: """Verify an anchor record""" if record.anchor_target == AnchorTarget.OPENTIMESTAMPS: return self._verify_opentimestamps(record) elif record.anchor_target == AnchorTarget.TSA: return self._verify_tsa(record) else: raise NotImplementedError(f"Verification for {record.anchor_target}") def _verify_opentimestamps(self, record: AnchorRecord) -> bool: """Verify OpenTimestamps proof""" # Use opentimestamps-client for verification # ots verify <proof_file> return True # Simplified def _verify_tsa(self, record: AnchorRecord) -> bool: """Verify TSA timestamp""" return True # Simplified Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: import requests import time from dataclasses import dataclass from typing import Optional from enum import Enum class AnchorTarget(Enum): BITCOIN = "bitcoin" OPENTIMESTAMPS = "opentimestamps" TSA = "tsa" @dataclass class AnchorRecord: merkle_root: str anchor_target: AnchorTarget anchor_timestamp: int anchor_proof: str # Transaction ID or TSA response class ExternalAnchor: """External anchoring for VCP Merkle Roots""" def __init__(self, target: AnchorTarget = AnchorTarget.OPENTIMESTAMPS): self.target = target def anchor(self, merkle_root: str) -> AnchorRecord: """Anchor a Merkle Root to external system""" if self.target == AnchorTarget.OPENTIMESTAMPS: return self._anchor_opentimestamps(merkle_root) elif self.target == AnchorTarget.TSA: return self._anchor_tsa(merkle_root) else: raise NotImplementedError(f"Anchor target {self.target} not implemented") def _anchor_opentimestamps(self, merkle_root: str) -> AnchorRecord: """ Anchor using OpenTimestamps (free, batched Bitcoin anchoring) Note: In production, use the official opentimestamps-client """ # This is a simplified example # Real implementation would use: pip install opentimestamps-client ots_url = "https://a.pool.opentimestamps.org/digest" response = requests.post( ots_url, data=bytes.fromhex(merkle_root), headers={'Content-Type': 'application/x-www-form-urlencoded'} ) if response.status_code == 200: return AnchorRecord( merkle_root=merkle_root, anchor_target=AnchorTarget.OPENTIMESTAMPS, anchor_timestamp=int(time.time()), anchor_proof=response.content.hex() ) else: raise Exception(f"OTS anchoring failed: {response.status_code}") def _anchor_tsa(self, merkle_root: str) -> AnchorRecord: """ Anchor using RFC 3161 Time Stamping Authority """ # RFC 3161 TSA request # In production, use a proper ASN.1 library tsa_url = "http://timestamp.digicert.com" # ... TSA implementation details ... raise NotImplementedError("TSA implementation requires ASN.1 library") def verify(self, record: AnchorRecord) -> bool: """Verify an anchor record""" if record.anchor_target == AnchorTarget.OPENTIMESTAMPS: return self._verify_opentimestamps(record) elif record.anchor_target == AnchorTarget.TSA: return self._verify_tsa(record) else: raise NotImplementedError(f"Verification for {record.anchor_target}") def _verify_opentimestamps(self, record: AnchorRecord) -> bool: """Verify OpenTimestamps proof""" # Use opentimestamps-client for verification # ots verify <proof_file> return True # Simplified def _verify_tsa(self, record: AnchorRecord) -> bool: """Verify TSA timestamp""" return True # Simplified COMMAND_BLOCK: import requests import time from dataclasses import dataclass from typing import Optional from enum import Enum class AnchorTarget(Enum): BITCOIN = "bitcoin" OPENTIMESTAMPS = "opentimestamps" TSA = "tsa" @dataclass class AnchorRecord: merkle_root: str anchor_target: AnchorTarget anchor_timestamp: int anchor_proof: str # Transaction ID or TSA response class ExternalAnchor: """External anchoring for VCP Merkle Roots""" def __init__(self, target: AnchorTarget = AnchorTarget.OPENTIMESTAMPS): self.target = target def anchor(self, merkle_root: str) -> AnchorRecord: """Anchor a Merkle Root to external system""" if self.target == AnchorTarget.OPENTIMESTAMPS: return self._anchor_opentimestamps(merkle_root) elif self.target == AnchorTarget.TSA: return self._anchor_tsa(merkle_root) else: raise NotImplementedError(f"Anchor target {self.target} not implemented") def _anchor_opentimestamps(self, merkle_root: str) -> AnchorRecord: """ Anchor using OpenTimestamps (free, batched Bitcoin anchoring) Note: In production, use the official opentimestamps-client """ # This is a simplified example # Real implementation would use: pip install opentimestamps-client ots_url = "https://a.pool.opentimestamps.org/digest" response = requests.post( ots_url, data=bytes.fromhex(merkle_root), headers={'Content-Type': 'application/x-www-form-urlencoded'} ) if response.status_code == 200: return AnchorRecord( merkle_root=merkle_root, anchor_target=AnchorTarget.OPENTIMESTAMPS, anchor_timestamp=int(time.time()), anchor_proof=response.content.hex() ) else: raise Exception(f"OTS anchoring failed: {response.status_code}") def _anchor_tsa(self, merkle_root: str) -> AnchorRecord: """ Anchor using RFC 3161 Time Stamping Authority """ # RFC 3161 TSA request # In production, use a proper ASN.1 library tsa_url = "http://timestamp.digicert.com" # ... TSA implementation details ... raise NotImplementedError("TSA implementation requires ASN.1 library") def verify(self, record: AnchorRecord) -> bool: """Verify an anchor record""" if record.anchor_target == AnchorTarget.OPENTIMESTAMPS: return self._verify_opentimestamps(record) elif record.anchor_target == AnchorTarget.TSA: return self._verify_tsa(record) else: raise NotImplementedError(f"Verification for {record.anchor_target}") def _verify_opentimestamps(self, record: AnchorRecord) -> bool: """Verify OpenTimestamps proof""" # Use opentimestamps-client for verification # ots verify <proof_file> return True # Simplified def _verify_tsa(self, record: AnchorRecord) -> bool: """Verify TSA timestamp""" return True # Simplified COMMAND_BLOCK: import hashlib import json from dataclasses import dataclass from typing import Dict, List, Any @dataclass class ModelGovernance: algo_id: str algo_version: str algo_type: str # AI_MODEL, RULE_BASED, HYBRID model_hash: str risk_classification: str last_approval_by: str approval_timestamp: int class VCPGovernance: """VCP-GOV module for algorithm governance""" def __init__(self): self.approved_hashes: set[str] = set() def compute_model_hash( self, model_code: bytes, parameters: Dict[str, Any], config: Dict[str, Any] ) -> str: """ Compute ModelHash from model components. Any change to code, parameters, or config changes the hash. """ canonical = json.dumps({ 'code_hash': hashlib.sha256(model_code).hexdigest(), 'parameters': parameters, 'config': config }, sort_keys=True, separators=(',', ':')) return f"sha256:{hashlib.sha256(canonical.encode()).hexdigest()}" def approve_model(self, model_hash: str, approver: str) -> bool: """Add model hash to approved registry""" self.approved_hashes.add(model_hash) return True def verify_execution(self, model_hash: str) -> bool: """ Verify model hash is in approved registry. Returns False if model was modified without approval. """ return model_hash in self.approved_hashes def create_gov_event( self, algo_id: str, model_hash: str, decision_factors: List[Dict], confidence_score: float ) -> Dict: """Create VCP-GOV event for logging""" is_approved = self.verify_execution(model_hash) return { "VCP-GOV": { "AlgorithmIdentification": { "AlgoID": algo_id, "ModelHash": model_hash, "ApprovalStatus": "APPROVED" if is_approved else "UNAPPROVED" }, "DecisionFactors": { "Features": decision_factors, "ConfidenceScore": confidence_score }, "AnomalyIndicators": { "UnapprovedExecution": not is_approved, "ParameterDrift": False, "CorrelationAnomaly": False } } } # Usage example gov = VCPGovernance() # Original model approval original_params = {"decorrelation_value": 0.85, "momentum_weight": 0.3} original_hash = gov.compute_model_hash( model_code=b"model_code_here", parameters=original_params, config={"version": "1.0"} ) gov.approve_model(original_hash, "RISK-MGR-007") print(f"Original hash: {original_hash}") print(f"Approved: {gov.verify_execution(original_hash)}") # Wu's manipulation manipulated_params = {"decorrelation_value": 0.02, "momentum_weight": 0.3} manipulated_hash = gov.compute_model_hash( model_code=b"model_code_here", parameters=manipulated_params, config={"version": "1.0"} ) print(f"\nManipulated hash: {manipulated_hash}") print(f"Approved: {gov.verify_execution(manipulated_hash)}") # FALSE! # Generate event showing the violation event = gov.create_gov_event( algo_id="wu-model-001", model_hash=manipulated_hash, decision_factors=[ {"Name": "decorrelation_value", "Value": "0.02", "Weight": "0.35"} ], confidence_score=0.87 ) print(f"\nUnapproved execution detected: {event['VCP-GOV']['AnomalyIndicators']['UnapprovedExecution']}") Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: import hashlib import json from dataclasses import dataclass from typing import Dict, List, Any @dataclass class ModelGovernance: algo_id: str algo_version: str algo_type: str # AI_MODEL, RULE_BASED, HYBRID model_hash: str risk_classification: str last_approval_by: str approval_timestamp: int class VCPGovernance: """VCP-GOV module for algorithm governance""" def __init__(self): self.approved_hashes: set[str] = set() def compute_model_hash( self, model_code: bytes, parameters: Dict[str, Any], config: Dict[str, Any] ) -> str: """ Compute ModelHash from model components. Any change to code, parameters, or config changes the hash. """ canonical = json.dumps({ 'code_hash': hashlib.sha256(model_code).hexdigest(), 'parameters': parameters, 'config': config }, sort_keys=True, separators=(',', ':')) return f"sha256:{hashlib.sha256(canonical.encode()).hexdigest()}" def approve_model(self, model_hash: str, approver: str) -> bool: """Add model hash to approved registry""" self.approved_hashes.add(model_hash) return True def verify_execution(self, model_hash: str) -> bool: """ Verify model hash is in approved registry. Returns False if model was modified without approval. """ return model_hash in self.approved_hashes def create_gov_event( self, algo_id: str, model_hash: str, decision_factors: List[Dict], confidence_score: float ) -> Dict: """Create VCP-GOV event for logging""" is_approved = self.verify_execution(model_hash) return { "VCP-GOV": { "AlgorithmIdentification": { "AlgoID": algo_id, "ModelHash": model_hash, "ApprovalStatus": "APPROVED" if is_approved else "UNAPPROVED" }, "DecisionFactors": { "Features": decision_factors, "ConfidenceScore": confidence_score }, "AnomalyIndicators": { "UnapprovedExecution": not is_approved, "ParameterDrift": False, "CorrelationAnomaly": False } } } # Usage example gov = VCPGovernance() # Original model approval original_params = {"decorrelation_value": 0.85, "momentum_weight": 0.3} original_hash = gov.compute_model_hash( model_code=b"model_code_here", parameters=original_params, config={"version": "1.0"} ) gov.approve_model(original_hash, "RISK-MGR-007") print(f"Original hash: {original_hash}") print(f"Approved: {gov.verify_execution(original_hash)}") # Wu's manipulation manipulated_params = {"decorrelation_value": 0.02, "momentum_weight": 0.3} manipulated_hash = gov.compute_model_hash( model_code=b"model_code_here", parameters=manipulated_params, config={"version": "1.0"} ) print(f"\nManipulated hash: {manipulated_hash}") print(f"Approved: {gov.verify_execution(manipulated_hash)}") # FALSE! # Generate event showing the violation event = gov.create_gov_event( algo_id="wu-model-001", model_hash=manipulated_hash, decision_factors=[ {"Name": "decorrelation_value", "Value": "0.02", "Weight": "0.35"} ], confidence_score=0.87 ) print(f"\nUnapproved execution detected: {event['VCP-GOV']['AnomalyIndicators']['UnapprovedExecution']}") COMMAND_BLOCK: import hashlib import json from dataclasses import dataclass from typing import Dict, List, Any @dataclass class ModelGovernance: algo_id: str algo_version: str algo_type: str # AI_MODEL, RULE_BASED, HYBRID model_hash: str risk_classification: str last_approval_by: str approval_timestamp: int class VCPGovernance: """VCP-GOV module for algorithm governance""" def __init__(self): self.approved_hashes: set[str] = set() def compute_model_hash( self, model_code: bytes, parameters: Dict[str, Any], config: Dict[str, Any] ) -> str: """ Compute ModelHash from model components. Any change to code, parameters, or config changes the hash. """ canonical = json.dumps({ 'code_hash': hashlib.sha256(model_code).hexdigest(), 'parameters': parameters, 'config': config }, sort_keys=True, separators=(',', ':')) return f"sha256:{hashlib.sha256(canonical.encode()).hexdigest()}" def approve_model(self, model_hash: str, approver: str) -> bool: """Add model hash to approved registry""" self.approved_hashes.add(model_hash) return True def verify_execution(self, model_hash: str) -> bool: """ Verify model hash is in approved registry. Returns False if model was modified without approval. """ return model_hash in self.approved_hashes def create_gov_event( self, algo_id: str, model_hash: str, decision_factors: List[Dict], confidence_score: float ) -> Dict: """Create VCP-GOV event for logging""" is_approved = self.verify_execution(model_hash) return { "VCP-GOV": { "AlgorithmIdentification": { "AlgoID": algo_id, "ModelHash": model_hash, "ApprovalStatus": "APPROVED" if is_approved else "UNAPPROVED" }, "DecisionFactors": { "Features": decision_factors, "ConfidenceScore": confidence_score }, "AnomalyIndicators": { "UnapprovedExecution": not is_approved, "ParameterDrift": False, "CorrelationAnomaly": False } } } # Usage example gov = VCPGovernance() # Original model approval original_params = {"decorrelation_value": 0.85, "momentum_weight": 0.3} original_hash = gov.compute_model_hash( model_code=b"model_code_here", parameters=original_params, config={"version": "1.0"} ) gov.approve_model(original_hash, "RISK-MGR-007") print(f"Original hash: {original_hash}") print(f"Approved: {gov.verify_execution(original_hash)}") # Wu's manipulation manipulated_params = {"decorrelation_value": 0.02, "momentum_weight": 0.3} manipulated_hash = gov.compute_model_hash( model_code=b"model_code_here", parameters=manipulated_params, config={"version": "1.0"} ) print(f"\nManipulated hash: {manipulated_hash}") print(f"Approved: {gov.verify_execution(manipulated_hash)}") # FALSE! # Generate event showing the violation event = gov.create_gov_event( algo_id="wu-model-001", model_hash=manipulated_hash, decision_factors=[ {"Name": "decorrelation_value", "Value": "0.02", "Weight": "0.35"} ], confidence_score=0.87 ) print(f"\nUnapproved execution detected: {event['VCP-GOV']['AnomalyIndicators']['UnapprovedExecution']}") CODE_BLOCK: Original hash: sha256:a1b2c3d4... Approved: True Manipulated hash: sha256:x9y8z7w6... Approved: False Unapproved execution detected: True Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: Original hash: sha256:a1b2c3d4... Approved: True Manipulated hash: sha256:x9y8z7w6... Approved: False Unapproved execution detected: True CODE_BLOCK: Original hash: sha256:a1b2c3d4... Approved: True Manipulated hash: sha256:x9y8z7w6... Approved: False Unapproved execution detected: True COMMAND_BLOCK: def detect_correlation_anomaly( model_predictions: List[float], other_model_predictions: List[List[float]], threshold: float = 0.95 ) -> bool: """ Detect if model predictions are suspiciously correlated with other models' predictions. """ import numpy as np for other_predictions in other_model_predictions: correlation = np.corrcoef(model_predictions, other_predictions)[0, 1] if abs(correlation) > threshold: return True # Anomaly detected! return False Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: def detect_correlation_anomaly( model_predictions: List[float], other_model_predictions: List[List[float]], threshold: float = 0.95 ) -> bool: """ Detect if model predictions are suspiciously correlated with other models' predictions. """ import numpy as np for other_predictions in other_model_predictions: correlation = np.corrcoef(model_predictions, other_predictions)[0, 1] if abs(correlation) > threshold: return True # Anomaly detected! return False COMMAND_BLOCK: def detect_correlation_anomaly( model_predictions: List[float], other_model_predictions: List[List[float]], threshold: float = 0.95 ) -> bool: """ Detect if model predictions are suspiciously correlated with other models' predictions. """ import numpy as np for other_predictions in other_model_predictions: correlation = np.corrcoef(model_predictions, other_predictions)[0, 1] if abs(correlation) > threshold: return True # Anomaly detected! return False COMMAND_BLOCK: import asyncio import aiohttp from typing import List, Dict from dataclasses import dataclass @dataclass class LogServer: url: str name: str @dataclass class DeliveryReceipt: server: str event_hash: str merkle_position: int timestamp: int signature: str class MultiLogReplicator: """ VCP v1.1 Multi-Log Replication REQ-ML-01: Send to at least N=2 log endpoints concurrently REQ-ML-02: Retain delivery receipts from ALL servers REQ-ML-03: Each server builds independent Merkle Tree """ def __init__(self, servers: List[LogServer], min_servers: int = 2): self.servers = servers self.min_servers = min_servers self.receipts: Dict[str, List[DeliveryReceipt]] = {} async def replicate_event(self, event: Dict) -> List[DeliveryReceipt]: """Send event to all log servers concurrently""" if len(self.servers) < self.min_servers: raise ValueError(f"Need at least {self.min_servers} log servers") async with aiohttp.ClientSession() as session: tasks = [ self._send_to_server(session, server, event) for server in self.servers ] receipts = await asyncio.gather(*tasks, return_exceptions=True) # Filter successful receipts valid_receipts = [r for r in receipts if isinstance(r, DeliveryReceipt)] if len(valid_receipts) < self.min_servers: raise Exception(f"Only {len(valid_receipts)} servers acknowledged") # Store receipts for later verification event_hash = event.get('event_hash', 'unknown') self.receipts[event_hash] = valid_receipts return valid_receipts async def _send_to_server( self, session: aiohttp.ClientSession, server: LogServer, event: Dict ) -> DeliveryReceipt: """Send event to single server and get receipt""" async with session.post( f"{server.url}/api/v1/events", json=event, timeout=aiohttp.ClientTimeout(total=5) ) as response: if response.status == 201: data = await response.json() return DeliveryReceipt( server=server.name, event_hash=event.get('event_hash', ''), merkle_position=data['merkle_position'], timestamp=data['timestamp'], signature=data['signature'] ) else: raise Exception(f"Server {server.name} returned {response.status}") def verify_consistency(self, event_hash: str) -> bool: """ Verify all servers recorded the same event. Detect split-view attacks. """ receipts = self.receipts.get(event_hash, []) if len(receipts) < 2: return False # All servers should have recorded the same event hash hashes = set(r.event_hash for r in receipts) return len(hashes) == 1 # Usage servers = [ LogServer("https://log1.vcp-network.io", "Primary"), LogServer("https://log2.vcp-network.io", "Secondary"), LogServer("https://log3.vcp-network.io", "Tertiary"), ] replicator = MultiLogReplicator(servers) async def log_trading_event(): event = { "event_hash": "abc123", "event_type": "PARAM_CHANGE", "parameter": "decorrelation_value", "old_value": 0.85, "new_value": 0.02, "timestamp": 1735520400000000 } receipts = await replicator.replicate_event(event) print(f"Event logged to {len(receipts)} servers") # Even if Wu controls one server, others have the record # Deleting from one server is detectable via cross-verification Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: import asyncio import aiohttp from typing import List, Dict from dataclasses import dataclass @dataclass class LogServer: url: str name: str @dataclass class DeliveryReceipt: server: str event_hash: str merkle_position: int timestamp: int signature: str class MultiLogReplicator: """ VCP v1.1 Multi-Log Replication REQ-ML-01: Send to at least N=2 log endpoints concurrently REQ-ML-02: Retain delivery receipts from ALL servers REQ-ML-03: Each server builds independent Merkle Tree """ def __init__(self, servers: List[LogServer], min_servers: int = 2): self.servers = servers self.min_servers = min_servers self.receipts: Dict[str, List[DeliveryReceipt]] = {} async def replicate_event(self, event: Dict) -> List[DeliveryReceipt]: """Send event to all log servers concurrently""" if len(self.servers) < self.min_servers: raise ValueError(f"Need at least {self.min_servers} log servers") async with aiohttp.ClientSession() as session: tasks = [ self._send_to_server(session, server, event) for server in self.servers ] receipts = await asyncio.gather(*tasks, return_exceptions=True) # Filter successful receipts valid_receipts = [r for r in receipts if isinstance(r, DeliveryReceipt)] if len(valid_receipts) < self.min_servers: raise Exception(f"Only {len(valid_receipts)} servers acknowledged") # Store receipts for later verification event_hash = event.get('event_hash', 'unknown') self.receipts[event_hash] = valid_receipts return valid_receipts async def _send_to_server( self, session: aiohttp.ClientSession, server: LogServer, event: Dict ) -> DeliveryReceipt: """Send event to single server and get receipt""" async with session.post( f"{server.url}/api/v1/events", json=event, timeout=aiohttp.ClientTimeout(total=5) ) as response: if response.status == 201: data = await response.json() return DeliveryReceipt( server=server.name, event_hash=event.get('event_hash', ''), merkle_position=data['merkle_position'], timestamp=data['timestamp'], signature=data['signature'] ) else: raise Exception(f"Server {server.name} returned {response.status}") def verify_consistency(self, event_hash: str) -> bool: """ Verify all servers recorded the same event. Detect split-view attacks. """ receipts = self.receipts.get(event_hash, []) if len(receipts) < 2: return False # All servers should have recorded the same event hash hashes = set(r.event_hash for r in receipts) return len(hashes) == 1 # Usage servers = [ LogServer("https://log1.vcp-network.io", "Primary"), LogServer("https://log2.vcp-network.io", "Secondary"), LogServer("https://log3.vcp-network.io", "Tertiary"), ] replicator = MultiLogReplicator(servers) async def log_trading_event(): event = { "event_hash": "abc123", "event_type": "PARAM_CHANGE", "parameter": "decorrelation_value", "old_value": 0.85, "new_value": 0.02, "timestamp": 1735520400000000 } receipts = await replicator.replicate_event(event) print(f"Event logged to {len(receipts)} servers") # Even if Wu controls one server, others have the record # Deleting from one server is detectable via cross-verification COMMAND_BLOCK: import asyncio import aiohttp from typing import List, Dict from dataclasses import dataclass @dataclass class LogServer: url: str name: str @dataclass class DeliveryReceipt: server: str event_hash: str merkle_position: int timestamp: int signature: str class MultiLogReplicator: """ VCP v1.1 Multi-Log Replication REQ-ML-01: Send to at least N=2 log endpoints concurrently REQ-ML-02: Retain delivery receipts from ALL servers REQ-ML-03: Each server builds independent Merkle Tree """ def __init__(self, servers: List[LogServer], min_servers: int = 2): self.servers = servers self.min_servers = min_servers self.receipts: Dict[str, List[DeliveryReceipt]] = {} async def replicate_event(self, event: Dict) -> List[DeliveryReceipt]: """Send event to all log servers concurrently""" if len(self.servers) < self.min_servers: raise ValueError(f"Need at least {self.min_servers} log servers") async with aiohttp.ClientSession() as session: tasks = [ self._send_to_server(session, server, event) for server in self.servers ] receipts = await asyncio.gather(*tasks, return_exceptions=True) # Filter successful receipts valid_receipts = [r for r in receipts if isinstance(r, DeliveryReceipt)] if len(valid_receipts) < self.min_servers: raise Exception(f"Only {len(valid_receipts)} servers acknowledged") # Store receipts for later verification event_hash = event.get('event_hash', 'unknown') self.receipts[event_hash] = valid_receipts return valid_receipts async def _send_to_server( self, session: aiohttp.ClientSession, server: LogServer, event: Dict ) -> DeliveryReceipt: """Send event to single server and get receipt""" async with session.post( f"{server.url}/api/v1/events", json=event, timeout=aiohttp.ClientTimeout(total=5) ) as response: if response.status == 201: data = await response.json() return DeliveryReceipt( server=server.name, event_hash=event.get('event_hash', ''), merkle_position=data['merkle_position'], timestamp=data['timestamp'], signature=data['signature'] ) else: raise Exception(f"Server {server.name} returned {response.status}") def verify_consistency(self, event_hash: str) -> bool: """ Verify all servers recorded the same event. Detect split-view attacks. """ receipts = self.receipts.get(event_hash, []) if len(receipts) < 2: return False # All servers should have recorded the same event hash hashes = set(r.event_hash for r in receipts) return len(hashes) == 1 # Usage servers = [ LogServer("https://log1.vcp-network.io", "Primary"), LogServer("https://log2.vcp-network.io", "Secondary"), LogServer("https://log3.vcp-network.io", "Tertiary"), ] replicator = MultiLogReplicator(servers) async def log_trading_event(): event = { "event_hash": "abc123", "event_type": "PARAM_CHANGE", "parameter": "decorrelation_value", "old_value": 0.85, "new_value": 0.02, "timestamp": 1735520400000000 } receipts = await replicator.replicate_event(event) print(f"Event logged to {len(receipts)} servers") # Even if Wu controls one server, others have the record # Deleting from one server is detectable via cross-verification COMMAND_BLOCK: @dataclass class GossipMessage: server_id: str merkle_root: str event_count: int timestamp: int signature: str class GossipProtocol: """ VCP v1.1 Gossip Protocol for Root Consistency Detects split-view attacks where different parties are shown different audit trails. """ def __init__(self, server_id: str, peers: List[str]): self.server_id = server_id self.peers = peers self.received_roots: Dict[str, List[GossipMessage]] = {} async def broadcast_root(self, root: str, event_count: int): """Broadcast our Merkle Root to all peers""" message = GossipMessage( server_id=self.server_id, merkle_root=root, event_count=event_count, timestamp=int(time.time()), signature=self._sign(root) ) # Send to all peers for peer in self.peers: await self._send_to_peer(peer, message) def receive_root(self, message: GossipMessage): """Process received Merkle Root from peer""" # Verify signature if not self._verify_signature(message): raise ValueError("Invalid signature") # Store for comparison key = f"{message.timestamp // 60}" # Group by minute if key not in self.received_roots: self.received_roots[key] = [] self.received_roots[key].append(message) # Check for discrepancies self._check_consistency(key) def _check_consistency(self, time_key: str): """Check if all servers report consistent roots""" messages = self.received_roots.get(time_key, []) if len(messages) < 2: return roots = set(m.merkle_root for m in messages) if len(roots) > 1: # ALERT: Split-view attack detected! self._raise_alert(time_key, messages) def _raise_alert(self, time_key: str, messages: List[GossipMessage]): """Handle detected inconsistency""" print(f"⚠️ ALERT: Merkle Root inconsistency at {time_key}") for msg in messages: print(f" - {msg.server_id}: {msg.merkle_root[:16]}...") Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: @dataclass class GossipMessage: server_id: str merkle_root: str event_count: int timestamp: int signature: str class GossipProtocol: """ VCP v1.1 Gossip Protocol for Root Consistency Detects split-view attacks where different parties are shown different audit trails. """ def __init__(self, server_id: str, peers: List[str]): self.server_id = server_id self.peers = peers self.received_roots: Dict[str, List[GossipMessage]] = {} async def broadcast_root(self, root: str, event_count: int): """Broadcast our Merkle Root to all peers""" message = GossipMessage( server_id=self.server_id, merkle_root=root, event_count=event_count, timestamp=int(time.time()), signature=self._sign(root) ) # Send to all peers for peer in self.peers: await self._send_to_peer(peer, message) def receive_root(self, message: GossipMessage): """Process received Merkle Root from peer""" # Verify signature if not self._verify_signature(message): raise ValueError("Invalid signature") # Store for comparison key = f"{message.timestamp // 60}" # Group by minute if key not in self.received_roots: self.received_roots[key] = [] self.received_roots[key].append(message) # Check for discrepancies self._check_consistency(key) def _check_consistency(self, time_key: str): """Check if all servers report consistent roots""" messages = self.received_roots.get(time_key, []) if len(messages) < 2: return roots = set(m.merkle_root for m in messages) if len(roots) > 1: # ALERT: Split-view attack detected! self._raise_alert(time_key, messages) def _raise_alert(self, time_key: str, messages: List[GossipMessage]): """Handle detected inconsistency""" print(f"⚠️ ALERT: Merkle Root inconsistency at {time_key}") for msg in messages: print(f" - {msg.server_id}: {msg.merkle_root[:16]}...") COMMAND_BLOCK: @dataclass class GossipMessage: server_id: str merkle_root: str event_count: int timestamp: int signature: str class GossipProtocol: """ VCP v1.1 Gossip Protocol for Root Consistency Detects split-view attacks where different parties are shown different audit trails. """ def __init__(self, server_id: str, peers: List[str]): self.server_id = server_id self.peers = peers self.received_roots: Dict[str, List[GossipMessage]] = {} async def broadcast_root(self, root: str, event_count: int): """Broadcast our Merkle Root to all peers""" message = GossipMessage( server_id=self.server_id, merkle_root=root, event_count=event_count, timestamp=int(time.time()), signature=self._sign(root) ) # Send to all peers for peer in self.peers: await self._send_to_peer(peer, message) def receive_root(self, message: GossipMessage): """Process received Merkle Root from peer""" # Verify signature if not self._verify_signature(message): raise ValueError("Invalid signature") # Store for comparison key = f"{message.timestamp // 60}" # Group by minute if key not in self.received_roots: self.received_roots[key] = [] self.received_roots[key].append(message) # Check for discrepancies self._check_consistency(key) def _check_consistency(self, time_key: str): """Check if all servers report consistent roots""" messages = self.received_roots.get(time_key, []) if len(messages) < 2: return roots = set(m.merkle_root for m in messages) if len(roots) > 1: # ALERT: Split-view attack detected! self._raise_alert(time_key, messages) def _raise_alert(self, time_key: str, messages: List[GossipMessage]): """Handle detected inconsistency""" print(f"⚠️ ALERT: Merkle Root inconsistency at {time_key}") for msg in messages: print(f" - {msg.server_id}: {msg.merkle_root[:16]}...") COMMAND_BLOCK: """ VCP v1.1 Complete Implementation Example Demonstrates: Hash chains, Merkle trees, external anchoring, governance """ import hashlib import json import time from dataclasses import dataclass, asdict from typing import List, Optional, Dict, Any from enum import Enum # ==================== EVENT TYPES ==================== class EventType(Enum): SIG = "SIG" # Signal generation ORD = "ORD" # Order submission ACK = "ACK" # Order acknowledged EXE = "EXE" # Execution REJ = "REJ" # Rejection PARAM = "PARAM" # Parameter change APPROVAL = "APPROVAL" # Model approval # ==================== VCP EVENT ==================== @dataclass class VCPEvent: event_id: str event_type: EventType timestamp_ns: int payload: Dict[str, Any] prev_hash: Optional[str] = None event_hash: Optional[str] = None def to_canonical(self) -> str: """RFC 8785 canonical JSON""" obj = { "event_id": self.event_id, "event_type": self.event_type.value, "timestamp_ns": self.timestamp_ns, "payload": self.payload, "prev_hash": self.prev_hash } return json.dumps(obj, sort_keys=True, separators=(',', ':')) def compute_hash(self) -> str: return hashlib.sha256(self.to_canonical().encode()).hexdigest() # ==================== VCP CHAIN ==================== class VCPChain: """Layer 1: Event Integrity via hash chain""" def __init__(self): self.events: List[VCPEvent] = [] self.latest_hash: Optional[str] = None def append(self, event: VCPEvent) -> VCPEvent: event.prev_hash = self.latest_hash event.event_hash = event.compute_hash() self.latest_hash = event.event_hash self.events.append(event) return event def verify(self) -> bool: prev = None for event in self.events: if event.prev_hash != prev: return False if event.event_hash != event.compute_hash(): return False prev = event.event_hash return True def get_hashes(self) -> List[str]: return [e.event_hash for e in self.events] # ==================== MERKLE TREE ==================== class MerkleTree: """Layer 2: Collection Integrity via RFC 6962 Merkle Tree""" @staticmethod def build(hashes: List[str]) -> str: """Build tree and return root""" if not hashes: return hashlib.sha256(b'').hexdigest() # Hash leaves with 0x00 prefix level = [ hashlib.sha256(b'\x00' + bytes.fromhex(h)).digest() for h in hashes ] # Build tree while len(level) > 1: next_level = [] for i in range(0, len(level), 2): left = level[i] right = level[i + 1] if i + 1 < len(level) else left combined = hashlib.sha256(b'\x01' + left + right).digest() next_level.append(combined) level = next_level return level[0].hex() # ==================== GOVERNANCE ==================== class ModelRegistry: """VCP-GOV: Cryptographic model governance""" def __init__(self): self.approved: Dict[str, Dict] = {} def compute_hash(self, params: Dict) -> str: canonical = json.dumps(params, sort_keys=True, separators=(',', ':')) return hashlib.sha256(canonical.encode()).hexdigest() def approve(self, model_id: str, params: Dict, approver: str) -> str: model_hash = self.compute_hash(params) self.approved[model_hash] = { "model_id": model_id, "params": params, "approver": approver, "timestamp": time.time_ns() } return model_hash def is_approved(self, params: Dict) -> bool: return self.compute_hash(params) in self.approved # ==================== COMPLETE SYSTEM ==================== class VCPAuditSystem: """Complete VCP v1.1 audit system""" def __init__(self): self.chain = VCPChain() self.registry = ModelRegistry() self.anchored_roots: List[Dict] = [] def approve_model(self, model_id: str, params: Dict, approver: str) -> str: """Approve a model configuration""" model_hash = self.registry.approve(model_id, params, approver) # Log the approval event = VCPEvent( event_id=f"approval-{int(time.time_ns())}", event_type=EventType.APPROVAL, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "model_hash": model_hash, "approver": approver } ) self.chain.append(event) return model_hash def log_signal( self, model_id: str, params: Dict, signal: str, confidence: float ) -> VCPEvent: """Log a trading signal with governance check""" is_approved = self.registry.is_approved(params) model_hash = self.registry.compute_hash(params) event = VCPEvent( event_id=f"sig-{int(time.time_ns())}", event_type=EventType.SIG, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "model_hash": model_hash, "signal": signal, "confidence": confidence, "governance": { "approved": is_approved, "anomaly_flags": { "unapproved_execution": not is_approved } } } ) return self.chain.append(event) def log_param_change( self, model_id: str, param_name: str, old_value: Any, new_value: Any ) -> VCPEvent: """Log a parameter change""" event = VCPEvent( event_id=f"param-{int(time.time_ns())}", event_type=EventType.PARAM, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "parameter": param_name, "old_value": old_value, "new_value": new_value } ) return self.chain.append(event) def create_anchor(self) -> Dict: """Create external anchor (Layer 3)""" hashes = self.chain.get_hashes() merkle_root = MerkleTree.build(hashes) anchor = { "merkle_root": merkle_root, "event_count": len(hashes), "timestamp": time.time_ns(), "anchor_target": "opentimestamps" # or bitcoin, tsa, etc. } self.anchored_roots.append(anchor) return anchor def verify_integrity(self) -> Dict: """Verify complete system integrity""" chain_valid = self.chain.verify() current_root = MerkleTree.build(self.chain.get_hashes()) return { "chain_valid": chain_valid, "current_merkle_root": current_root, "event_count": len(self.chain.events), "anchored_roots": len(self.anchored_roots) } # ==================== DEMONSTRATION ==================== def simulate_two_sigma_scenario(): """ Simulate the Two Sigma incident with VCP Shows how manipulation would be detected immediately """ print("=" * 60) print("VCP v1.1 Two Sigma Scenario Simulation") print("=" * 60) system = VCPAuditSystem() # Step 1: Approve original model print("\n[1] Approving original model with decorrelation=0.85...") original_params = { "decorrelation_value": 0.85, "momentum_weight": 0.3, "risk_limit": 0.02 } original_hash = system.approve_model("wu-model-001", original_params, "RISK-MGR-007") print(f" Model hash: {original_hash[:16]}...") print(f" Status: APPROVED ✓") # Step 2: Generate signals with approved model print("\n[2] Generating signal with approved model...") event = system.log_signal( model_id="wu-model-001", params=original_params, signal="LONG", confidence=0.87 ) approved = event.payload["governance"]["approved"] print(f" Signal: LONG (confidence: 0.87)") print(f" Governance check: {'PASSED ✓' if approved else 'FAILED ✗'}") # Step 3: Wu's manipulation - change parameter without approval print("\n[3] ATTACK: Changing decorrelation parameter to 0.02...") system.log_param_change( model_id="wu-model-001", param_name="decorrelation_value", old_value=0.85, new_value=0.02 ) print(" Parameter change LOGGED (hash chain updated)") # Step 4: Try to generate signal with manipulated model print("\n[4] Generating signal with manipulated model...") manipulated_params = { "decorrelation_value": 0.02, # Changed! "momentum_weight": 0.3, "risk_limit": 0.02 } event = system.log_signal( model_id="wu-model-001", params=manipulated_params, signal="LONG", confidence=0.91 ) approved = event.payload["governance"]["approved"] unapproved_flag = event.payload["governance"]["anomaly_flags"]["unapproved_execution"] print(f" Signal: LONG (confidence: 0.91)") print(f" Governance check: {'PASSED ✓' if approved else 'FAILED ✗'}") print(f" ⚠️ UNAPPROVED EXECUTION DETECTED: {unapproved_flag}") # Step 5: Create anchor print("\n[5] Creating external anchor...") anchor = system.create_anchor() print(f" Merkle root: {anchor['merkle_root'][:16]}...") print(f" Events anchored: {anchor['event_count']}") # Step 6: Verify integrity print("\n[6] Verifying system integrity...") status = system.verify_integrity() print(f" Hash chain valid: {status['chain_valid']}") print(f" Total events: {status['event_count']}") print(f" Anchored checkpoints: {status['anchored_roots']}") print("\n" + "=" * 60) print("RESULT: With VCP, Wu's manipulation was detected IMMEDIATELY") print(" at step 4, when the unapproved model was executed.") print(" No 4-year detection delay. No $165M client losses.") print("=" * 60) if __name__ == "__main__": simulate_two_sigma_scenario() Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: """ VCP v1.1 Complete Implementation Example Demonstrates: Hash chains, Merkle trees, external anchoring, governance """ import hashlib import json import time from dataclasses import dataclass, asdict from typing import List, Optional, Dict, Any from enum import Enum # ==================== EVENT TYPES ==================== class EventType(Enum): SIG = "SIG" # Signal generation ORD = "ORD" # Order submission ACK = "ACK" # Order acknowledged EXE = "EXE" # Execution REJ = "REJ" # Rejection PARAM = "PARAM" # Parameter change APPROVAL = "APPROVAL" # Model approval # ==================== VCP EVENT ==================== @dataclass class VCPEvent: event_id: str event_type: EventType timestamp_ns: int payload: Dict[str, Any] prev_hash: Optional[str] = None event_hash: Optional[str] = None def to_canonical(self) -> str: """RFC 8785 canonical JSON""" obj = { "event_id": self.event_id, "event_type": self.event_type.value, "timestamp_ns": self.timestamp_ns, "payload": self.payload, "prev_hash": self.prev_hash } return json.dumps(obj, sort_keys=True, separators=(',', ':')) def compute_hash(self) -> str: return hashlib.sha256(self.to_canonical().encode()).hexdigest() # ==================== VCP CHAIN ==================== class VCPChain: """Layer 1: Event Integrity via hash chain""" def __init__(self): self.events: List[VCPEvent] = [] self.latest_hash: Optional[str] = None def append(self, event: VCPEvent) -> VCPEvent: event.prev_hash = self.latest_hash event.event_hash = event.compute_hash() self.latest_hash = event.event_hash self.events.append(event) return event def verify(self) -> bool: prev = None for event in self.events: if event.prev_hash != prev: return False if event.event_hash != event.compute_hash(): return False prev = event.event_hash return True def get_hashes(self) -> List[str]: return [e.event_hash for e in self.events] # ==================== MERKLE TREE ==================== class MerkleTree: """Layer 2: Collection Integrity via RFC 6962 Merkle Tree""" @staticmethod def build(hashes: List[str]) -> str: """Build tree and return root""" if not hashes: return hashlib.sha256(b'').hexdigest() # Hash leaves with 0x00 prefix level = [ hashlib.sha256(b'\x00' + bytes.fromhex(h)).digest() for h in hashes ] # Build tree while len(level) > 1: next_level = [] for i in range(0, len(level), 2): left = level[i] right = level[i + 1] if i + 1 < len(level) else left combined = hashlib.sha256(b'\x01' + left + right).digest() next_level.append(combined) level = next_level return level[0].hex() # ==================== GOVERNANCE ==================== class ModelRegistry: """VCP-GOV: Cryptographic model governance""" def __init__(self): self.approved: Dict[str, Dict] = {} def compute_hash(self, params: Dict) -> str: canonical = json.dumps(params, sort_keys=True, separators=(',', ':')) return hashlib.sha256(canonical.encode()).hexdigest() def approve(self, model_id: str, params: Dict, approver: str) -> str: model_hash = self.compute_hash(params) self.approved[model_hash] = { "model_id": model_id, "params": params, "approver": approver, "timestamp": time.time_ns() } return model_hash def is_approved(self, params: Dict) -> bool: return self.compute_hash(params) in self.approved # ==================== COMPLETE SYSTEM ==================== class VCPAuditSystem: """Complete VCP v1.1 audit system""" def __init__(self): self.chain = VCPChain() self.registry = ModelRegistry() self.anchored_roots: List[Dict] = [] def approve_model(self, model_id: str, params: Dict, approver: str) -> str: """Approve a model configuration""" model_hash = self.registry.approve(model_id, params, approver) # Log the approval event = VCPEvent( event_id=f"approval-{int(time.time_ns())}", event_type=EventType.APPROVAL, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "model_hash": model_hash, "approver": approver } ) self.chain.append(event) return model_hash def log_signal( self, model_id: str, params: Dict, signal: str, confidence: float ) -> VCPEvent: """Log a trading signal with governance check""" is_approved = self.registry.is_approved(params) model_hash = self.registry.compute_hash(params) event = VCPEvent( event_id=f"sig-{int(time.time_ns())}", event_type=EventType.SIG, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "model_hash": model_hash, "signal": signal, "confidence": confidence, "governance": { "approved": is_approved, "anomaly_flags": { "unapproved_execution": not is_approved } } } ) return self.chain.append(event) def log_param_change( self, model_id: str, param_name: str, old_value: Any, new_value: Any ) -> VCPEvent: """Log a parameter change""" event = VCPEvent( event_id=f"param-{int(time.time_ns())}", event_type=EventType.PARAM, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "parameter": param_name, "old_value": old_value, "new_value": new_value } ) return self.chain.append(event) def create_anchor(self) -> Dict: """Create external anchor (Layer 3)""" hashes = self.chain.get_hashes() merkle_root = MerkleTree.build(hashes) anchor = { "merkle_root": merkle_root, "event_count": len(hashes), "timestamp": time.time_ns(), "anchor_target": "opentimestamps" # or bitcoin, tsa, etc. } self.anchored_roots.append(anchor) return anchor def verify_integrity(self) -> Dict: """Verify complete system integrity""" chain_valid = self.chain.verify() current_root = MerkleTree.build(self.chain.get_hashes()) return { "chain_valid": chain_valid, "current_merkle_root": current_root, "event_count": len(self.chain.events), "anchored_roots": len(self.anchored_roots) } # ==================== DEMONSTRATION ==================== def simulate_two_sigma_scenario(): """ Simulate the Two Sigma incident with VCP Shows how manipulation would be detected immediately """ print("=" * 60) print("VCP v1.1 Two Sigma Scenario Simulation") print("=" * 60) system = VCPAuditSystem() # Step 1: Approve original model print("\n[1] Approving original model with decorrelation=0.85...") original_params = { "decorrelation_value": 0.85, "momentum_weight": 0.3, "risk_limit": 0.02 } original_hash = system.approve_model("wu-model-001", original_params, "RISK-MGR-007") print(f" Model hash: {original_hash[:16]}...") print(f" Status: APPROVED ✓") # Step 2: Generate signals with approved model print("\n[2] Generating signal with approved model...") event = system.log_signal( model_id="wu-model-001", params=original_params, signal="LONG", confidence=0.87 ) approved = event.payload["governance"]["approved"] print(f" Signal: LONG (confidence: 0.87)") print(f" Governance check: {'PASSED ✓' if approved else 'FAILED ✗'}") # Step 3: Wu's manipulation - change parameter without approval print("\n[3] ATTACK: Changing decorrelation parameter to 0.02...") system.log_param_change( model_id="wu-model-001", param_name="decorrelation_value", old_value=0.85, new_value=0.02 ) print(" Parameter change LOGGED (hash chain updated)") # Step 4: Try to generate signal with manipulated model print("\n[4] Generating signal with manipulated model...") manipulated_params = { "decorrelation_value": 0.02, # Changed! "momentum_weight": 0.3, "risk_limit": 0.02 } event = system.log_signal( model_id="wu-model-001", params=manipulated_params, signal="LONG", confidence=0.91 ) approved = event.payload["governance"]["approved"] unapproved_flag = event.payload["governance"]["anomaly_flags"]["unapproved_execution"] print(f" Signal: LONG (confidence: 0.91)") print(f" Governance check: {'PASSED ✓' if approved else 'FAILED ✗'}") print(f" ⚠️ UNAPPROVED EXECUTION DETECTED: {unapproved_flag}") # Step 5: Create anchor print("\n[5] Creating external anchor...") anchor = system.create_anchor() print(f" Merkle root: {anchor['merkle_root'][:16]}...") print(f" Events anchored: {anchor['event_count']}") # Step 6: Verify integrity print("\n[6] Verifying system integrity...") status = system.verify_integrity() print(f" Hash chain valid: {status['chain_valid']}") print(f" Total events: {status['event_count']}") print(f" Anchored checkpoints: {status['anchored_roots']}") print("\n" + "=" * 60) print("RESULT: With VCP, Wu's manipulation was detected IMMEDIATELY") print(" at step 4, when the unapproved model was executed.") print(" No 4-year detection delay. No $165M client losses.") print("=" * 60) if __name__ == "__main__": simulate_two_sigma_scenario() COMMAND_BLOCK: """ VCP v1.1 Complete Implementation Example Demonstrates: Hash chains, Merkle trees, external anchoring, governance """ import hashlib import json import time from dataclasses import dataclass, asdict from typing import List, Optional, Dict, Any from enum import Enum # ==================== EVENT TYPES ==================== class EventType(Enum): SIG = "SIG" # Signal generation ORD = "ORD" # Order submission ACK = "ACK" # Order acknowledged EXE = "EXE" # Execution REJ = "REJ" # Rejection PARAM = "PARAM" # Parameter change APPROVAL = "APPROVAL" # Model approval # ==================== VCP EVENT ==================== @dataclass class VCPEvent: event_id: str event_type: EventType timestamp_ns: int payload: Dict[str, Any] prev_hash: Optional[str] = None event_hash: Optional[str] = None def to_canonical(self) -> str: """RFC 8785 canonical JSON""" obj = { "event_id": self.event_id, "event_type": self.event_type.value, "timestamp_ns": self.timestamp_ns, "payload": self.payload, "prev_hash": self.prev_hash } return json.dumps(obj, sort_keys=True, separators=(',', ':')) def compute_hash(self) -> str: return hashlib.sha256(self.to_canonical().encode()).hexdigest() # ==================== VCP CHAIN ==================== class VCPChain: """Layer 1: Event Integrity via hash chain""" def __init__(self): self.events: List[VCPEvent] = [] self.latest_hash: Optional[str] = None def append(self, event: VCPEvent) -> VCPEvent: event.prev_hash = self.latest_hash event.event_hash = event.compute_hash() self.latest_hash = event.event_hash self.events.append(event) return event def verify(self) -> bool: prev = None for event in self.events: if event.prev_hash != prev: return False if event.event_hash != event.compute_hash(): return False prev = event.event_hash return True def get_hashes(self) -> List[str]: return [e.event_hash for e in self.events] # ==================== MERKLE TREE ==================== class MerkleTree: """Layer 2: Collection Integrity via RFC 6962 Merkle Tree""" @staticmethod def build(hashes: List[str]) -> str: """Build tree and return root""" if not hashes: return hashlib.sha256(b'').hexdigest() # Hash leaves with 0x00 prefix level = [ hashlib.sha256(b'\x00' + bytes.fromhex(h)).digest() for h in hashes ] # Build tree while len(level) > 1: next_level = [] for i in range(0, len(level), 2): left = level[i] right = level[i + 1] if i + 1 < len(level) else left combined = hashlib.sha256(b'\x01' + left + right).digest() next_level.append(combined) level = next_level return level[0].hex() # ==================== GOVERNANCE ==================== class ModelRegistry: """VCP-GOV: Cryptographic model governance""" def __init__(self): self.approved: Dict[str, Dict] = {} def compute_hash(self, params: Dict) -> str: canonical = json.dumps(params, sort_keys=True, separators=(',', ':')) return hashlib.sha256(canonical.encode()).hexdigest() def approve(self, model_id: str, params: Dict, approver: str) -> str: model_hash = self.compute_hash(params) self.approved[model_hash] = { "model_id": model_id, "params": params, "approver": approver, "timestamp": time.time_ns() } return model_hash def is_approved(self, params: Dict) -> bool: return self.compute_hash(params) in self.approved # ==================== COMPLETE SYSTEM ==================== class VCPAuditSystem: """Complete VCP v1.1 audit system""" def __init__(self): self.chain = VCPChain() self.registry = ModelRegistry() self.anchored_roots: List[Dict] = [] def approve_model(self, model_id: str, params: Dict, approver: str) -> str: """Approve a model configuration""" model_hash = self.registry.approve(model_id, params, approver) # Log the approval event = VCPEvent( event_id=f"approval-{int(time.time_ns())}", event_type=EventType.APPROVAL, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "model_hash": model_hash, "approver": approver } ) self.chain.append(event) return model_hash def log_signal( self, model_id: str, params: Dict, signal: str, confidence: float ) -> VCPEvent: """Log a trading signal with governance check""" is_approved = self.registry.is_approved(params) model_hash = self.registry.compute_hash(params) event = VCPEvent( event_id=f"sig-{int(time.time_ns())}", event_type=EventType.SIG, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "model_hash": model_hash, "signal": signal, "confidence": confidence, "governance": { "approved": is_approved, "anomaly_flags": { "unapproved_execution": not is_approved } } } ) return self.chain.append(event) def log_param_change( self, model_id: str, param_name: str, old_value: Any, new_value: Any ) -> VCPEvent: """Log a parameter change""" event = VCPEvent( event_id=f"param-{int(time.time_ns())}", event_type=EventType.PARAM, timestamp_ns=time.time_ns(), payload={ "model_id": model_id, "parameter": param_name, "old_value": old_value, "new_value": new_value } ) return self.chain.append(event) def create_anchor(self) -> Dict: """Create external anchor (Layer 3)""" hashes = self.chain.get_hashes() merkle_root = MerkleTree.build(hashes) anchor = { "merkle_root": merkle_root, "event_count": len(hashes), "timestamp": time.time_ns(), "anchor_target": "opentimestamps" # or bitcoin, tsa, etc. } self.anchored_roots.append(anchor) return anchor def verify_integrity(self) -> Dict: """Verify complete system integrity""" chain_valid = self.chain.verify() current_root = MerkleTree.build(self.chain.get_hashes()) return { "chain_valid": chain_valid, "current_merkle_root": current_root, "event_count": len(self.chain.events), "anchored_roots": len(self.anchored_roots) } # ==================== DEMONSTRATION ==================== def simulate_two_sigma_scenario(): """ Simulate the Two Sigma incident with VCP Shows how manipulation would be detected immediately """ print("=" * 60) print("VCP v1.1 Two Sigma Scenario Simulation") print("=" * 60) system = VCPAuditSystem() # Step 1: Approve original model print("\n[1] Approving original model with decorrelation=0.85...") original_params = { "decorrelation_value": 0.85, "momentum_weight": 0.3, "risk_limit": 0.02 } original_hash = system.approve_model("wu-model-001", original_params, "RISK-MGR-007") print(f" Model hash: {original_hash[:16]}...") print(f" Status: APPROVED ✓") # Step 2: Generate signals with approved model print("\n[2] Generating signal with approved model...") event = system.log_signal( model_id="wu-model-001", params=original_params, signal="LONG", confidence=0.87 ) approved = event.payload["governance"]["approved"] print(f" Signal: LONG (confidence: 0.87)") print(f" Governance check: {'PASSED ✓' if approved else 'FAILED ✗'}") # Step 3: Wu's manipulation - change parameter without approval print("\n[3] ATTACK: Changing decorrelation parameter to 0.02...") system.log_param_change( model_id="wu-model-001", param_name="decorrelation_value", old_value=0.85, new_value=0.02 ) print(" Parameter change LOGGED (hash chain updated)") # Step 4: Try to generate signal with manipulated model print("\n[4] Generating signal with manipulated model...") manipulated_params = { "decorrelation_value": 0.02, # Changed! "momentum_weight": 0.3, "risk_limit": 0.02 } event = system.log_signal( model_id="wu-model-001", params=manipulated_params, signal="LONG", confidence=0.91 ) approved = event.payload["governance"]["approved"] unapproved_flag = event.payload["governance"]["anomaly_flags"]["unapproved_execution"] print(f" Signal: LONG (confidence: 0.91)") print(f" Governance check: {'PASSED ✓' if approved else 'FAILED ✗'}") print(f" ⚠️ UNAPPROVED EXECUTION DETECTED: {unapproved_flag}") # Step 5: Create anchor print("\n[5] Creating external anchor...") anchor = system.create_anchor() print(f" Merkle root: {anchor['merkle_root'][:16]}...") print(f" Events anchored: {anchor['event_count']}") # Step 6: Verify integrity print("\n[6] Verifying system integrity...") status = system.verify_integrity() print(f" Hash chain valid: {status['chain_valid']}") print(f" Total events: {status['event_count']}") print(f" Anchored checkpoints: {status['anchored_roots']}") print("\n" + "=" * 60) print("RESULT: With VCP, Wu's manipulation was detected IMMEDIATELY") print(" at step 4, when the unapproved model was executed.") print(" No 4-year detection delay. No $165M client losses.") print("=" * 60) if __name__ == "__main__": simulate_two_sigma_scenario() CODE_BLOCK: ============================================================ VCP v1.1 Two Sigma Scenario Simulation ============================================================ [1] Approving original model with decorrelation=0.85... Model hash: a3f8b2c9d1e4f5a6... Status: APPROVED ✓ [2] Generating signal with approved model... Signal: LONG (confidence: 0.87) Governance check: PASSED ✓ [3] ATTACK: Changing decorrelation parameter to 0.02... Parameter change LOGGED (hash chain updated) [4] Generating signal with manipulated model... Signal: LONG (confidence: 0.91) Governance check: FAILED ✗ ⚠️ UNAPPROVED EXECUTION DETECTED: True [5] Creating external anchor... Merkle root: 7f2e9d8c6b5a4f31... Events anchored: 4 [6] Verifying system integrity... Hash chain valid: True Total events: 4 Anchored checkpoints: 1 ============================================================ RESULT: With VCP, Wu's manipulation was detected IMMEDIATELY at step 4, when the unapproved model was executed. No 4-year detection delay. No $165M client losses. ============================================================ Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: ============================================================ VCP v1.1 Two Sigma Scenario Simulation ============================================================ [1] Approving original model with decorrelation=0.85... Model hash: a3f8b2c9d1e4f5a6... Status: APPROVED ✓ [2] Generating signal with approved model... Signal: LONG (confidence: 0.87) Governance check: PASSED ✓ [3] ATTACK: Changing decorrelation parameter to 0.02... Parameter change LOGGED (hash chain updated) [4] Generating signal with manipulated model... Signal: LONG (confidence: 0.91) Governance check: FAILED ✗ ⚠️ UNAPPROVED EXECUTION DETECTED: True [5] Creating external anchor... Merkle root: 7f2e9d8c6b5a4f31... Events anchored: 4 [6] Verifying system integrity... Hash chain valid: True Total events: 4 Anchored checkpoints: 1 ============================================================ RESULT: With VCP, Wu's manipulation was detected IMMEDIATELY at step 4, when the unapproved model was executed. No 4-year detection delay. No $165M client losses. ============================================================ CODE_BLOCK: ============================================================ VCP v1.1 Two Sigma Scenario Simulation ============================================================ [1] Approving original model with decorrelation=0.85... Model hash: a3f8b2c9d1e4f5a6... Status: APPROVED ✓ [2] Generating signal with approved model... Signal: LONG (confidence: 0.87) Governance check: PASSED ✓ [3] ATTACK: Changing decorrelation parameter to 0.02... Parameter change LOGGED (hash chain updated) [4] Generating signal with manipulated model... Signal: LONG (confidence: 0.91) Governance check: FAILED ✗ ⚠️ UNAPPROVED EXECUTION DETECTED: True [5] Creating external anchor... Merkle root: 7f2e9d8c6b5a4f31... Events anchored: 4 [6] Verifying system integrity... Hash chain valid: True Total events: 4 Anchored checkpoints: 1 ============================================================ RESULT: With VCP, Wu's manipulation was detected IMMEDIATELY at step 4, when the unapproved model was executed. No 4-year detection delay. No $165M client losses. ============================================================ COMMAND_BLOCK: # Clone the spec git clone https://github.com/veritaschain/vcp-spec.git # Python SDK (coming soon) pip install vcp-core # TypeScript SDK (coming soon) npm install @veritaschain/vcp-core Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: # Clone the spec git clone https://github.com/veritaschain/vcp-spec.git # Python SDK (coming soon) pip install vcp-core # TypeScript SDK (coming soon) npm install @veritaschain/vcp-core COMMAND_BLOCK: # Clone the spec git clone https://github.com/veritaschain/vcp-spec.git # Python SDK (coming soon) pip install vcp-core # TypeScript SDK (coming soon) npm install @veritaschain/vcp-core - The Two Sigma Incident: What Actually Happened - Why Traditional Logs Failed - VCP v1.1: The Three-Layer Architecture - Layer 1: Event Integrity with Hash Chains - Layer 2: Collection Integrity with Merkle Trees - Layer 3: External Verifiability with Anchoring - VCP-GOV: Cryptographic Model Governance - Multi-Log Replication: Defeating Omission Attacks - Code Examples: Building a VCP Event Stream - Regulatory Compliance: MiFID II, EU AI Act, SEC Rule 17a-4 - Performance Benchmarks - Getting Started with VCP - Wu's model runs with decorrelation_value: 0.85 → recorded with hash_A - Wu changes parameter to 0.02 → this creates event with hash_B - Any verification shows hash_B ≠ hash_A - Detection is immediate - Leaf nodes = hashes of individual events - Internal nodes = hashes of their children - Root = single hash representing the entire set - Wu deletes the database entry - Hash chain is rebuilt without that event - Auditors see a valid chain - Original Merkle Root was computed including the modification event - Root was externally anchored (Layer 3) - Deleting the event changes the Merkle Root - Verification against anchored root fails - Omission detected - Build a fake hash chain with manipulated events - Construct a valid Merkle Tree over the fake events - Present this as authentic - Bitcoin blockchain (most secure) - OpenTimestamps (free, batched Bitcoin anchoring) - RFC 3161 TSAs (timestamp authorities) - Ethereum (alternative blockchain) - All historical Merkle Roots were anchored to Bitcoin - Bitcoin transactions are immutable - Wu cannot alter blockchain history - Modified logs fail verification against anchored roots - Post-hoc manipulation is mathematically impossible - ✅ Automatic event recording - ✅ Tamper-evident hash chains - ✅ Merkle Tree completeness proofs - ✅ External anchoring for third-party verification - Complete timestamped audit trail - Ability to reconstruct original records - AI inventory documentation → VCP-GOV AlgorithmIdentification - Model governance → ModelHash verification - Change management → Hash chain records all changes - Specification: VCP v1.1 Spec - IETF Draft: draft-kamimura-scitt-vcp - Website: veritaschain.org - Contact: [email protected] - Hash chains detect event modification - Merkle trees detect event omission - External anchoring prevents post-hoc manipulation - ModelHash detects unauthorized model changes - Multi-log replication defeats single-point compromise