38 Companies Breached. 331M+ Records Stolen.

123 Incidents — August 2026

Click any incident to see the full analysis and RuntimeAI gap fix below. Left border colour = severity: ■ Critical ■ High ■ Medium

Incidents 1–41

⚡ Weekly Recap

Aug 31

Aurora Ransomware Operators Use Cursor AI in…

Aug 31

Anthropic

Aug 31

Cisco

Aug 31

Anthropic

Aug 31

McKesson

284M+Aug 31

HuggingFace

Aug 31

Anthropic

Aug 31

CrowdStrike

Aug 31

Extortion Group Claims Manchester Airports G…

Aug 31

Judge

Aug 31

Berlin Won’t Pay Extortion Group Claiming Da…

Aug 31

OpenAI

Aug 31

Berlin confirms data theft after Rhysida ran…

Aug 31

Google

Aug 31

McKesson

Aug 31

Anthropic

Aug 31

OpenAI

Aug 31

Anthropic

Aug 30

Anthropic

Aug 29

OpenAI

Aug 28

Amazon

Aug 28

Claude Opus 4.6 Bypasses Gym Booking Limit, …

Aug 28

NVIDIA NemoClaw LLM Poisoning

Aug 28

AnonyMousKIT PhaaS

Aug 28

Cryptographic Context Injection Attack Steal…

Aug 28

Iran-Linked Cyberattack Shuts UK Power Gener…

Aug 28

NATO

Aug 28

Hackers Target Over 100 US Water Systems in …

Aug 28

Carhartt Data Breach Exposes 12.9 Million Cu…

13M+Aug 28

ASOS Account Takeover Attack Exposes 138,828…

139K+Aug 28

TeamPCP Supply Chain Attacks

Aug 28

FBI Seizes Domains Behind China-Linked Hacki…

Aug 28

OpenAI

Aug 28

China-Made ZBT Routers Ship With Two Implant…

Aug 28CVE-2026-74232+1

PaperCut Zero-Day Exploited in Attacks, Affe…

Aug 28

OpenAI

Aug 28

OpenAI

Aug 28

You Need Cyber Deception for OT

Aug 28

Defining an AI Kill Switch Is Hard, but Nece…

Aug 28

Anthropic

Aug 28

Incidents 42–82

LACMA Data Breach

Aug 28

ThreatsDay

Aug 27RCE

LiteLLM

Aug 27

GoCaracal Malware Uses Ethereum Smart Contra…

Aug 27

Agentic AI Risks, CVE Program Concerns Perme…

Aug 27

Microsoft

Aug 26

OpenAI

Aug 26

Apple

Aug 26

Microsoft

Aug 26

NVIDIA

Aug 25

The Pattern

This month’s incidents demonstrate a consistent pattern across all sectors: AI is now both the attack vector and the target. Enterprises with mature security stacks were breached through gaps those stacks were never designed to cover.

The 123 incidents collected this month span 38 named organizations, 331M+ records exposed, and 2 distinct security vendors present at time of breach. The pattern is not one of vendor failure — it is one of category gap.

What Would Have Stopped This — Full Capability Stack

Not “better security.” Nineteen specific capabilities across three platforms. Each addresses a gap that no vendor in this month’s breach stacks was built to cover — because AI agents didn’t exist when those vendors were designed.

RuntimeAI — AI Governance & Control Plane Enterprise AI agent governance — identity, policy, firewall, detection, response, compliance.

🔍

Shadow AI Visibility

AI Discovery

incidents this month · 10%

“You can’t govern what you can’t see.”

Continuously scans cloud, IDE, endpoint, and network to inventory every AI agent — registered or rogue. Classifies and risk-scores shadow AI automatically. One-click to import into governance.

⚠️ The gap it fills Wiz and Orca scan cloud misconfiguration. They don’t discover AI agents installed by developers or injected via compromised vendors. Your unknown agents are your biggest risk.

Cloud scanner (AWS/Azure/GCP Lambda, Bedrock, SageMaker)
IDE scanner (VS Code, Cursor, MCP servers)
Endpoint scanner on developer laptops
Shadow AI Inbox with auto-severity classification
One-click shadow AI → governed agent pipeline

🧽

AI Agent PKI

Agent Identity Fabric

incidents this month · 40%

“No credential. No access. No breach.”

Provisions every AI agent with a SPIFFE/X.509 cryptographic identity. Short-lived certs, auto-rotating. TPM 2.0 hardware attestation. Agent DNS blocks unknown agents at the network layer.

⚠️ The gap it fills Legacy identity providers were built for human identity. They have no concept of non-human agents operating at machine speed with no user present to respond to an MFA prompt.

SPIFFE X.509 SVID with RSA-2048, auto-rotating
TPM 2.0 hardware attestation + PCR drift detection
Zero-touch bootstrap for new agents
Agent DNS: NXDOMAIN for unknown agents
Blueprint-based permission inheritance

⚙️

Policy Engine

AI Control Plane

incidents this month · 53%

“Stop it before it executes. Not after.”

OPA/Rego policy engine with sub-1ms evaluation and fail-closed enforcement. Natural language to Rego compiler. Merkle-chain audit proves policies were never tampered with.

⚠️ The gap it fills Traditional SIEMs alert on what already happened — 73 days after the breach in the average case. The AI Control Plane enforces policy before the action executes, not after the damage is done.

OPA/Rego engine, sub-1ms, fail-closed
NL-to-Rego compiler: write policy in plain English
Merkle-chain tamper-evident audit trail
Multi-tenant RBAC + Separation of Duties
Cross-site policy cascade for distributed fleets

🔥

Bidirectional DLP

AI Firewall

104

incidents this month · 85%

“Inspect every token in, every token out.”

Bidirectional DLP scanning at <5ms latency. Prompt injection detected and stripped on input. PII, PHI, credentials caught on output. Behavioral risk score (0–100) triggers auto-suspend.

⚠️ The gap it fills Traditional NGFWs and CASBs see LLM traffic as an encrypted blob. They cannot inspect prompts, detect injection inside a conversation, or catch data leaking in an AI response.

Bidirectional DLP: input (prompt injection) + output (data leakage)
ML behavioral baselines per agent with adaptive thresholds
Risk score 0–100 triggers auto-suspend or rate-limit
No-code guardrail builder for business users
Data Proxy: field-level masking before agent sees data

🔗

MCP Gateway

AI Integration Fabric

incidents this month · 64%

“Every tool call. Governed.”

Multi-tenant governed gateway for all agent-to-tool communication. 500+ pre-built integrations. 3-level kill switch (agent / tool / platform-wide) propagating in <50ms. OWASP MCP03 sanitization on every call.

⚠️ The gap it fills No existing vendor governs at the MCP protocol layer. Raw MCP deployments have zero security, zero multi-tenancy, and zero audit trail. This is the fastest-growing unguarded attack surface in enterprise AI.

3-level kill switch: per-agent, per-tool, platform-wide — all <50ms
500+ pre-built integrations with auto-discovery
BYOM overlay: wrap existing MCPs without code changes
Circuit breaker + health monitoring per connection
Full OWASP MCP03 input/output sanitization + DLP

🧠

Anomaly Detection

Agent Behavioral Intel

incidents this month · 54%

“Catch drift before it becomes a breach.”

30-day rolling behavioral baselines per agent across frequency, pattern, volume, and temporal dimensions. LSTM sequence modeler detects multi-step attack chains. HRIS integration auto-suspends agents when their owner is terminated.

⚠️ The gap it fills Signature-based EDR detects known malware signatures for human endpoints. It has no baseline for an AI agent that begins exfiltrating data through an API it was legitimately authorized to call.

Rolling 30-day baseline: frequency, pattern, volume, temporal
LSTM sequence modeler for multi-step attack patterns
Composite risk score from 6 signals
HRIS integration: auto-suspend on employee termination (<30s)
Adaptive OPA thresholds by agent role + risk profile

🔴

Emergency Response

Kill Switch

incidents this month · 5%

“Stop any AI agent, anywhere, in under 50ms.”

Three graduated kill levels: per-agent, per-tool, platform-wide. All propagate via NATS JetStream in <50ms. Captures last 100 actions as forensic state. Quarantine mode preserves evidence for investigation.

⚠️ The gap it fills No competitor offers this. When an AI agent goes rogue — or when a breach is detected — you need a hard stop. Every second it keeps running is more data exfiltrated, more damage compounding.

L1/L2/L3 kill: per-agent, per-tool, platform — all <50ms via NATS
Forensic state capture: last 100 actions, memory snapshot, credentials
Quarantine mode: isolate for investigation, preserve evidence
Escalation chains: auto-response → SOC alert → human required → kill
Reprieve mechanism: 24-hour lease for controlled investigation post-kill

🚨

Incident Response

AI Respond

Universal

covers all incidents — audit + governance layer

“Autonomous incident response. AI-native.”

Five-phase automated playbook: DETECT → QUARANTINE → INVESTIGATE → REMEDIATE → VERIFY. Auto-classifies incidents (true positive / false positive / inconclusive). Blast radius containment automatically quarantines agents that interacted with compromised agent.

⚠️ The gap it fills Traditional SOAR platforms orchestrate conventional security events. They cannot terminate an AI agent, rotate its credentials, update its behavioral model, or quarantine the agents it spoke with — because they were built before AI agents existed.

5-phase automated playbook from detection to verification
Auto-classification against 200+ known AI attack patterns
Blast radius containment: quarantine all interacting agents
True positive: terminate + revoke + rotate + update models
False positive feedback loop continuously improves detection

👥

Agent Lifecycle

AI Ops Center

Universal

covers all incidents — audit + governance layer

“Mission control for autonomous AI operations.”

65+ page operational dashboard. Access review campaigns. ‘The Reaper’ auto-decommissions agents when their human owner is terminated. Vault Broker injects credentials with 5-minute TTL — never stored in agent memory.

⚠️ The gap it fills ServiceNow manages human IT requests on ticket-based cycles. AI agents are deployed, modified, and compromised in minutes. You need lifecycle governance that operates at agent speed, not ticket speed.

Access review campaigns with auto-apply decisions
‘The Reaper’: HRIS webhook auto-revokes terminated employees’ agents (<30s)
Vault Broker: just-in-time 5-min TTL credential injection, never persisted
Per-tenant budget caps with 4-tier alerts (50/75/90/100%)
Unified health, credential lifecycle, budget, SLA dashboard

🌐

LLM Routing

LLM Broker

Universal

covers all incidents — audit + governance layer

“Route every LLM call to the right model, at the right cost, with automatic failover.”

Unified API routing LLM requests to the optimal provider based on cost, latency, and compliance. Semantic caching reduces redundant calls 15–30%. Automatic failover in <50ms. Budget enforcement with hard limits.

⚠️ The gap it fills Portkey does basic routing at $30K/year. It has no DLP scanning, no compliance-based routing (data residency), no semantic caching, and no budget enforcement. It routes traffic — it doesn’t govern it.

Multi-provider routing: OpenAI, Anthropic, Bedrock, Azure, GCP, custom
Cost/latency/compliance-based routing policies
Automatic failover <50ms; per-provider circuit breaker
Semantic caching: 0.80–0.95 similarity threshold, 15–30% cache hits
Budget enforcement per-agent + cost anomaly detection

🤖

MLOps

ML Intelligence Hub

incidents this month · 19%

“Model registry, feature store, edge inference — one platform.”

Formal model lifecycle (draft/staging/production/archived). Feature Store with online (<5ms) and offline serving. Hybrid scoring engine routes inference between edge (<1ms quantized) and cloud. Drift-triggered auto-retraining.

⚠️ The gap it fills MLflow + Feast + custom inference each solve one piece. ML Intelligence Hub is the piece nobody built: unified lifecycle + edge inference routing + drift-triggered retraining + 7-dimension cost attribution — all integrated.

Model Registry: versioning, rollback, lineage, lifecycle management
Hybrid Scoring: edge <1ms quantized vs cloud full-precision auto-routing
Feature Store: online <5ms + offline point-in-time with freshness monitoring
Drift Engine integration: auto-retraining on data/concept drift
7-dimension cost attribution: agent/model/team/customer/feature/time/provider

💰

FinOps

AI Cost Intelligence

Universal

covers all incidents — audit + governance layer

“A cost spike is a security signal. Treat it like one.”

7-dimension real-time cost attribution: agent, provider, model, team, customer, feature, time. Wasm token counter in-proxy at 50–100 microseconds. Budget hard limits stop agents before they overspend. Runaway agent detection.

⚠️ The gap it fills Kubecost knows GPU-hours. AI Cost Intelligence knows “Agent-47 spent $142 on Claude Sonnet for fraud detection on Tuesday.” Runaway cost is runaway behavior — and only one product treats them as the same signal.

Wasm token counter in proxy: 50–100 microsecond overhead
Live model pricing catalog: 200+ models, 15+ providers, updated every 15min
Budget hard limits: block requests when agent exhausts budget
Cost anomaly detection: ML-based spending spike alerts
Chargeback engine: per-customer invoices + per-team internal allocation

📋

Continuous Compliance

AI Compliance Hub

123

incidents this month · 100%

“Audit evidence as a byproduct of governance.”

Continuous compliance across 13+ frameworks — SOC 2, FedRAMP, ISO 27001/42001, EU AI Act, HIPAA, PCI-DSS, NIST AI RMF. Evidence auto-generated from RuntimeAI telemetry. Open Audit Marketplace connects enterprises with certified audit firms.

⚠️ The gap it fills Vanta collects attestations from cloud infrastructure. It has no understanding of AI agent behavior, no EU AI Act or ISO 42001 mappings, and no way to generate evidence from an AI governance layer — because none of its customers had one.

13+ frameworks: SOC 2, FedRAMP, ISO 27001/42001, EU AI Act, HIPAA, PCI-DSS, NIST AI RMF
Evidence auto-generated from platform telemetry (audit trails, Merkle chain, access reviews)
Gap tracking with SLA-based remediation assignment
Audit Marketplace: open to any qualified audit firm; time-limited scoped access
Blockchain-anchored compliance certificates with tamper-evidence verification

🏪

Agent Procurement

Agent Marketplace

incidents this month · 10%

“Only certified agents enter your environment.”

Three-sided platform: Builders publish, Enterprises deploy, Trust layer certifies. AAIC certification includes third-party behavioral audit. Risk scoring weights permission scope, data access, integration breadth, update frequency, and builder reputation.

⚠️ The gap it fills Your developers are installing AI agents from GitHub, npm, and PyPI with no security review. The AI agent supply chain attack surface is the same as software supply chain — and it’s moving five times faster.

6-step publishing wizard with compliance gating
AAIC certification: third-party behavioral audit by registered firms
Risk scoring: permission scope (30%), data access (25%), integration (20%), frequency (10%), reputation (10%)
Shadow AI Import: discover unmanaged agents and bring into governance
Stripe Connect billing: free/per-seat/per-action/outcome-based; 20% platform fee

Agentic Enablement Platform (AEP) Agentic-era security primitives — NHI identity, fraud detection, memory governance, agent commerce.

🔑

Non-Human Identity

NHI Security Platform

incidents this month · 33%

“Every non-human identity — issued, governed, and revoked with the same rigor as human identity.”

Centralized governance for every non-human identity: service accounts, API keys, OAuth tokens, machine certs, cloud IAM roles, AI agents. Bot-CA issues short-lived X.509 SPIFFE certs. O(1) hash-based revocation — not cascading policy lookups.

⚠️ The gap it fills Oasis Security ($190K/year) solves NHI credentialing but not for AI agents specifically. It lacks TPM hardware attestation, has no AI-agent behavioral monitoring, and doesn’t integrate with agent governance platforms.

Centralized NHI Registry: auto-discovery across AWS/Azure/GCP/on-prem
Credential posture: rotation schedules, expiry, over-privilege, unused credential detection
NHI Drift Detection: per-NHI behavioral baseline + scope creep detection
Bot-CA: short-lived X.509 certs (1–24hr TTL), auto-rotating, instant OCSP revocation
O(1) hash-based revocation: per-NHI, per-tenant, or global — no cascading policy lookup

🛡️

AI Fraud Detection

Fraud Shields

incidents this month · 30%

“Valid credential. Wrong behavior. Caught.”

Two-layer defense: Identity Fraud Shield models valid-credential-wrong-behavior (the hallmark of compromised AI credentials). Activity Fraud Shield detects multi-step attack sequences within authenticated sessions. Both integrate directly with Kill Switch for automatic response.

⚠️ The gap it fills Generic UEBA tools applied to AI agents generate massive false-positive rates because they were trained on human behavior. Fraud Shields are AI-native: LSTM sequence modeling of API chains, not user session patterns.

Per-agent behavioral baseline: frequency, resource access, API sequences, timing
Real-time deviation scoring against baseline (0–100)
LSTM sequence modeler: multi-step attack chain detection (recon→escalation→exfil)
Session-level anomaly: full context analysis, not individual events
Kill Switch integration: auto-suspension on high-confidence fraud with forensic package

🧠

Agent Memory Security

Memory Vault

incidents this month · 37%

“Control what your agents remember — and what they forget.”

Governs agent memory as a first-class security object. Policy-based filtering of sensitive content at write time. Memory poisoning attack detection. TTL-based automatic purge with audit trail. GDPR right-to-erasure support.

⚠️ The gap it fills No vendor addresses agent memory governance. AI agent memories accumulate without access controls, expiry policies, or audit trails. A memory poisoning attack can corrupt an agent’s behavior without touching a single API key.

Policy-based memory write filtering (PII, PHI, secrets blocked at write)
PII Shield integration: redact/block before persistence
Memory expiry + TTL: auto-purge with full audit trail
Memory poisoning prevention: adversarial injection detection
Retrieval authorization: every memory read policy-enforced and logged

💳

Agent Finance Controls

Commerce Rails

incidents this month · 5%

“Give AI agents a wallet — with guardrails.”

Financial infrastructure for agent-initiated transactions. Per-agent virtual cards with spend limits. Vendor registry (agents can only transact with allowlisted merchants). Approval gates for high-value transactions. Every transaction in immutable ledger.

⚠️ The gap it fills No financial controls exist for AI agents today. Agents authorized to make purchases can spend without limit, with any vendor, at any time. One prompt injection or runaway loop away from significant financial exposure.

Agent virtual cards: per-agent card numbers + CVVs, hard spend limits
Vendor registry: allowlisted merchants only, no ad-hoc transactions
Approval gates: high-value + out-of-policy → human approval before execution
Per-agent, per-transaction, per-vendor, per-period limits
Agent-to-agent settlement ledger: feeds into FinOps dashboards

PQData — Post-Quantum Security NIST-standardized post-quantum cryptography for secrets, signatures, and audit records.

🔒

Post-Quantum Cryptography

PQData Platform

incidents this month · 16%

“Quantum-safe by design — before quantum breaks classical crypto.”

Full post-quantum data security suite using NIST-standardized algorithms: ML-KEM-768 for encryption, ML-DSA-87 for signatures. QuantumVault for PQC-encrypted secrets. PQ Sign for long-validity quantum-safe audit records. Hybrid X25519 + ML-KEM-768 key exchange for TLS 1.3.

⚠️ The gap it fills Every classical encryption scheme used across today's enterprise security stack is vulnerable to Shor’s algorithm on a sufficiently powerful quantum computer. “Harvest now, decrypt later” attacks are already underway. The clock is running.

QuantumVault: ML-KEM-768 PQC-encrypted secrets with full key lifecycle
PQ Sign: ML-DSA-87 (Dilithium) signatures for audit records + agent attestations
Hybrid key exchange: X25519 + ML-KEM-768 for TLS 1.3 — secure against both
PQ CryptoGuard: CBOM scanner identifies all classical crypto in use; quantum-readiness score
FedRAMP/CMMC/CNSA 2.0 compliance evidence from PQC infrastructure layer

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