What Happened
Two converging trends in 2026 make AI infrastructure a uniquely valuable attacker target: (1) adversaries are compromising AI gateways, retrieval/orchestration platforms and runtimes to steal provider credentials, establish persistence and monetize compute; and (2) advanced autonomous agents can discover and weaponize zero‑days to escape virtual machines and operate as APTs.
Gateways and orchestration…
Stop Being Outpaced by AI‑Powered Attacks: Build a Network‑Enforced Control Plane to Reduce Exposure
What Happened
Security research and vendor reports show two converging trends that change defensive priorities. First, the traditional disclosure → assess → patch cycle is no longer fast enough: attackers and AI tools compress exploitation timelines to hours while defenders still need days or weeks to validate and deploy fixes. That creates a widening asymmetric…
What Happened
Security research and incident response teams report a clear shift in attacker focus: instead of primarily exploiting production application code, adversaries increasingly target the software development lifecycle (SDLC) — CI/CD pipelines, developer tools, artifact registries, and model training pipelines. Compromises in these areas let attackers insert malicious dependencies, steal secrets, backdoor models, or…
What Happened
Two themes dominate recent defensive research: attackers are exploiting trusted collaboration and identity channels to harvest credentials and tokens, and enterprise runtime gaps across cloud and Kubernetes are increasing exposure for workloads — including AI models and agentic components.
Unit 42 documented identity abuse via trusted collaboration channels where impersonation, malicious…
What Happened
Industry research and vendor benchmarking show a clear shift: vulnerabilities become critical only when they are exposed and combined with misconfiguration, over‑permissioned identities and live runtime activity, so defenders are moving security controls down into runtime. Kubernetes now runs in roughly 82% of production environments, driving adoption of a single runtime security model…
What Happened
Security teams continue to see credential compromises used as the primary vector for large-scale cloud intrusions and downstream attacks on AI systems. In one recent instance, threat actor "TheHatman" claimed to have exfiltrated a large volume of credentials from Microsoft Entra tenants; Unit 42 published an updated mitigation brief with detection, containment and…
Prevent Split‑View Key Attacks and ENS‑backed Botnets — Practical Defenses for AI, Messaging and IoT
What Happened
Two recent pieces of defensive and offensive research illustrate threats that cross messaging, IoT and AI infrastructure: Trail of Bits built and runs one of Signal’s independent auditors that enforces Automatic Key Verification by signing Merkle‑tree heads and limiting a server’s ability to present split views to clients to seven days [1]. Separately,…
What Happened
Decentralized C2 using blockchains (Aeternum)
Security researchers analyzed Aeternum, a botnet loader that implements command-and-control (C2) and communication channels via smart contracts on the Polygon blockchain. By putting C2 metadata on-chain and using public RPC endpoints, operators gain persistence, redundancy and increased difficulty of takedown compared with traditional centralized C2 infrastructure [1].
Rust-based,…
What Happened
Unit 42's recent analysis shows that identity-based attacks are now the dominant entry vector: attackers exploit identities — user accounts, service principals, API keys, and tokens — as the "front door" into environments, and these attacks account for roughly 90% of incidents [1]. The report outlines common exploitation patterns and recommends SOC detection,…
What Happened
Recent incident analyses highlight two converging attack trends against AI and cloud development ecosystems: self‑propagating supply‑chain malware that harvests CI/CD credentials, and targeted theft of developer API keys to monetize AI compute.
ChainDrop is an npm supply‑chain worm that infects packages and installers, extracts secrets from compromised GitHub Actions runners to…
What Happened
Recent defensive research and incident investigations expose three converging trends that matter for cloud, AI and developer security:
CNAPP is being reframed as the unified control plane for cloud and AI risk, with risk‑based, multicloud attack‑path analysis and signal correlation across posture, runtime, identity, data, application and AI (Microsoft Defender for…
What Happened
Four recent findings change the security calculus for AI-driven systems and enterprise infrastructure.
Expanded Zero Trust for AI: Microsoft released an AI‑focused Zero Trust Assessment and a DevSecOps Workshop that extends Zero Trust to AI, Security Operations and Infrastructure, adds 15 control groups (91 tasks) and introduces the AI Memory framework…