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Security audit

Capability Evolver Pro

Security checks for vulnerabilities and agentic risk

Overview

The skill is a coherent local log-analysis and recommendation tool, with a real but limited risk from weak validation of large or malformed log inputs.

This appears suitable for local log analysis, but only provide logs you intend the skill to inspect. Avoid feeding untrusted, extremely large, or malformed log arrays until the skill enforces its documented limits and validates each log entry field.

Vulnerability Patterns
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (1)

T09 · Insecure Skill Coding Practices

Warning
Location
handler.ts:91
Finding

Unvalidated and Unbounded Log Input Enables Denial of Service

Content
View full analysis
Remediation
View remediation
MAX_LOGS) { errors.push(`"logs" must contain no more than ${MAX_LOGS} entries`); } ``` 2. Validate every log entry using a strict schema: - Require each entry to be a non-null object. - Require `timestamp` and `message` to be strings. - Restrict `level` to `error`, `warn`, `info`, or `debug`. - Permit `context` and `stack` only when they are strings. - Reject unexpected or structurally invalid values. 3. Bound attacker-controlled strings, for example: - `message`: 4,096 characters. - `context`: 512 characters. - `stack`: a documented, defensible maximum. - `timestamp`: a short ISO-8601 string. 4. Validate timestamps with strict parsing and reject invalid values before analysis. 5. Apply a request-body size limit at the Agent or runtime boundary so oversized payloads are rejected before allocation and deserialization. 6. Avoid repeated full-array scans where practical. Compute error, warning, and slow-operation counts during a single bounded pass. 7. Return structured validation errors rather than relying on runtime exceptions from operations such as `.slice()`. 8. Add tests covering null fields, missing fields, invalid levels, oversized strings, more than 10,000 entries, sparse arrays, and non-object array elements. ]]>
Vulnerability Patterns
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (4)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The skill description uses broad activation cues like analyzing logs, diagnosing failures, improving reliability, and assessing system health without strong scoping constraints. In agent frameworks that auto-select skills from natural language, this can cause unintended invocation, exposing runtime logs or steering agent behavior into self-modification workflows when the user did not explicitly request this skill.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The 'When to Use' section contains vague phrases such as 'what's failing', 'improve my agent', and 'check system health' that are common in ordinary conversation and can over-match unrelated requests. Because this is a meta-skill for diagnostics and self-improvement, accidental activation is more dangerous than for a narrow utility skill: it may pull in sensitive logs, influence operational decisions, or initiate automated evolution steps.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The package description uses very broad trigger language such as analyzing logs, diagnosing failures, improving reliability, and assessing system health, which can overlap with many common user requests. In an agent ecosystem, this increases the chance the skill is invoked in unintended contexts, potentially giving a powerful self-modification or meta-analysis capability access to inputs and decisions outside its narrowly intended scope.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
92% confidence
Finding

This code file contains user-facing natural-language strings in Chinese for action descriptions while the rest of the skill metadata is in English. Because the skill does not offer language selection or explain that it is intended for a Chinese-speaking context, it may violate a language/locale policy requiring user opt-in or clear justification.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.