T05 · Unauthorized Access and Privilege Escalation
- Location
SKILL.md:175- Finding
Overbroad Access to Persistent Agent State and Personal Knowledge Stores
- Content
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- Remediation
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Security audit
Security checks for vulnerabilities and agentic risk
This is a research-methodology skill, but it asks agents to use broad local notes, persistent memory, recurring automation, sub-agents, and a hard-coded private search endpoint without enough user control.
Review before installing. Use this only in a tightly sandboxed workspace, disable or narrow alwaysActive activation, approve any filesystem locations explicitly, avoid broad personal vault or home-directory reads, configure search endpoints yourself instead of using the hard-coded private address, and require confirmation before cron, heartbeat, sub-agent, notification, MEMORY.md, or TASKS.md changes.
SKILL.md:175Overbroad Access to Persistent Agent State and Personal Knowledge Stores
references/sourcing-strategies.md:19Hard-Coded Private-Network Search Endpoint May Disclose Research Queries
The declared description presents the skill as an active deep-research methodology that performs substantive research tasks and produces exhaustive cited reports. The supplied code chunk does not implement any research functionality. Instead, it is a repository/skill validation utility focused on file existence, metadata checks, reference-file presence, and a basic secret scan. This is a materially different primary purpose from the declared behavior, so it should be flagged as a mismatch.
The skill is configured as alwaysActive while also describing a very broad 'ANY domain' research capability. That combination can cause the skill to activate in many contexts beyond clear user intent, increasing the chance of unsolicited tool usage, instruction hijacking of normal conversations into research workflows, or unnecessary exposure of user prompts to search tools.
Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.
- [ ] Weekly: Review token costs, check for anomalies
- [ ] Weekly: Audit task completion rates
- [ ] Monthly: Archive old memory logs, consolidate MEMORY.md
- [ ] Monthly: Update skills, check for security advisories
- [ ] Quarterly: Review HEARTBEAT.md relevance
- [ ] Quarterly: Evaluate model stack (new models available?)
Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
2. Least privilege: Allowlist mode, unlisted binaries trigger `ask:always`
3. Write scoping: Operations constrained to `$WORKSPACE_ROOT`
4. HITL for side-effects: Manual approval for state changes/network calls
5. Path traversal prevention: Strict workspace root prevents .ssh/.env access
**Prompt injection remains an unsolved problem across all agent frameworks.**
Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
- No citations or self-referential
- Anonymous without demonstrated expertise
- Methodology absent or vague
- Absolutist claims without caveats
- Hidden funding/affiliations
- Contradicted by primary evidence
The trigger phrase 'When research is requested' is ambiguous and can match a wide range of ordinary user requests. In an agent setting, ambiguous activation conditions can cause the skill to overtake normal assistant behavior, initiate unnecessary file loads or searches, and broaden collection of external data without sufficiently explicit consent.
The instruction to output as an "Obsidian-ready .md file" with mandatory YAML frontmatter forces a specific format regardless of user preference. This is a natural-language policy concern because it imposes a workflow/output constraint without offering the user a choice or opt-in.
The skill explicitly instructs writes to persistent memory and task files in autonomous contexts without requiring a user-facing warning or confirmation. Persistent writes can alter future agent behavior, store sensitive user data, create unintended long-lived state, and be abused for covert persistence or workflow manipulation if the skill is triggered unexpectedly.
The activation criteria for adversarial analysis are broad and subjective, such as 'contested topics,' 'institutional behavior,' or 'suspicious patterns.' In an autonomous or semi-autonomous research workflow, this can cause the agent to over-apply adversarial lenses, increasing false suppression narratives, distrust amplification, and biased evidence interpretation.
The 'counter-intelligence for researchers' section introduces adversarial framing and defensive tactics that exceed the declared purpose of systematic research. Even without explicit malicious commands, this normalizes covert-thinking patterns and operational caution that can be repurposed for evasion or for escalating suspicious interpretations in ambiguous situations.
The guidance to vary search patterns, use low-telemetry tools, and archive evidence moves beyond neutral research methodology into operational tradecraft for reducing observability. In a general-purpose agent skill, this can help users or downstream agents conduct sensitive investigations while intentionally avoiding monitoring, which is not necessary for ordinary report generation and broadens misuse potential.
Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.
- Session key: `agent + channel + scope + peer`
**Compaction (Context Window Management):**
When sessions exceed context window, OpenClaw compacts (summarizes/truncates) older messages.
**What Compaction Destroys:**
- File paths and exact commands
The example for the description field says to write the trigger phrase like "describing to a coworker in chat," which encourages natural conversational phrasing rather than narrow activation language. In a markdown reference about skill authoring, this can lead authors to create broad triggers that overlap with everyday speech and increase accidental invocation risk.
The guidance says to use "words users actually type" for trigger matching, but it does not define boundaries for how specific those words must be or what kinds of common phrases to avoid. Without explicit exclusion rules or negative examples, authors may choose vague phrases that collide with ordinary requests.
Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
2. Classify: permission, dependency, config, or logic failure
3. Isolate: disable optional steps, test smallest failing unit
4. Confirm: one fix at a time, re-run same test
5. Document: write cause/fix into SKILL.md guardrails
**Session Snapshot Gotcha:**
OpenClaw snapshots skills when session starts. Config changes may need new session.
The template instructs authors to use a generic 'description field' for how users ask for the task and even suggests '[trigger phrase matching user language]' without requiring narrow phrases, scope limits, or negative examples. This can lead to skill manifests that match broad everyday language and cause unintended invocation.
The rubric hard-codes politically loaded categories like 'state propaganda' and 'institutional narrative enforcement' into a universal credibility scoring system, which biases evaluation before evidence is assessed. In a research skill, this can systematically steer an agent toward distrusting authoritative or institutional sources and overvaluing contrarian narratives, degrading neutrality and increasing susceptibility to misinformation or conspiratorial framing.
Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.
1. CONTEXT CHECK → Existing knowledge base / prior research
2. QUERY ELABORATION → Expand scope, plan search strategy
3. MULTI-SOURCE → Gather from diverse sources (40-80+ for deep)
4. PATTERN ANALYSIS → Cross-domain recognition, temporal/actor/info flow
5. CREDIBILITY SCORE → 0-10 scale on ALL sources, merit-based
The instruction 'Load when researching proactive agents, workflow orchestration, or autonomous system design' is broad and lacks clear boundaries or exclusion conditions. Phrases like 'workflow orchestration' and 'autonomous system design' can apply to many ordinary tasks, increasing the chance of unintended invocation of this reference skill.
The standard report template hard-codes 'methodology: k-deep-research-v2', and the same pattern appears in other sections and references. This imposes a specific organizational convention in the output format without documenting opt-in, alternatives, or why the constraint is required for all uses.
No suspicious patterns detected.