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01/08/2026 10:46 pm
TL;DR: Anthropic’s Claude Mythos research showed AI can autonomously discover thousands of vulnerabilities and generate working exploits at machine speed, compressing the time between vulnerability discovery and weaponisation, according to Torq. The practical consequence is that manual SOC triage and containment assumptions are no longer durable when attackers can move faster than human response chains.
NHIMG editorial — based on content published by torq: LLMjacking: How Attackers Hijack AI Using Compromised NHIs
Questions worth separating out
Q: How should security teams handle machine-speed attacks that outrun manual SOC triage?
A: They should predefine bounded containment actions, remove unnecessary handoffs, and let automation handle low-risk steps immediately.
Q: Why do AI-assisted attacks increase the importance of privileged access governance?
A: AI speeds up reconnaissance, phishing, and post-compromise actions, but attackers still need usable access paths to do real damage.
Q: What breaks when SOC response still depends on human approval at every step?
A: The response loop breaks because the attacker can complete discovery, exploitation, and lateral movement before analysts finish coordination.
Practitioner guidance
- Define response authority before the incident starts Pre-authorise which containment actions an automated workflow may take, which require human approval, and which must never be executed without review.
- Reduce handoffs in detection-to-containment paths Map every manual transfer between SIEM, SOAR, EDR, cloud, and identity teams, then eliminate steps that only reformat context.
- Treat privileged identities as fast-moving attack paths Review service accounts, API keys, and delegated tokens for the ability to move laterally before the SOC can react.
What's in the full article
Torq's full article covers the operational detail this post intentionally leaves for the source:
- How the Torq AI SOC Platform organises multi-agent triage, investigation, containment, and case management
- Examples of autonomous response guardrails and how the vendor scopes approved actions
- Deployment examples showing how the vendor claims teams reduced MTTR and moved legacy SOAR workflows
- The product-specific workflow for translating natural-language intent into production agents
👉 Read Torq's analysis of Claude Mythos and AI-speed SOC response →
AI-speed threats and the SOC response gap: what changes now?
Explore further
01/08/2026 10:55 pm
Machine-speed attack economics have exposed a governance gap, not just a tooling gap. The article’s central claim is that AI can compress discovery, exploit creation, and attacker decision-making into a cycle that human-operated SOCs cannot match. That shifts security from alert handling to control design, especially where identity, secrets, and delegated access can be abused as the fastest route to impact. Practitioners should treat response latency as a governance metric, not an operational inconvenience.
A question worth separating out:
Q: Who is accountable when automated response actions contain an incident incorrectly?
A: Accountability remains with the organisation’s security leadership and control owners, not the automation itself. Teams need clear approval boundaries, audit logs, and rollback procedures so every action can be traced to an owner and a rule. That is especially important when the workflow touches identity, access, or system isolation.
👉 Read our full editorial: Claude Mythos and the collapse of manual SOC response models
