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Security audit

Super Proactive V2

Security checks for vulnerabilities and agentic risk

Overview

This skill is transparent about being a proactive memory system, but it asks the agent to persist broad session details and run recurring autonomous tasks without clear limits or approval boundaries.

Install only if you intentionally want an agent to maintain persistent project memory and act proactively. Before use, limit what may be written to memory, forbid secrets and personal data, require approval for scheduled or queue-driven actions, and define how to review, pause, and delete the created files.

Vulnerability Patterns
  • System PersistenceInstalls backdoors, hooks, services, or scheduled tasks that survive the run
  • 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
Findings (2)

T09 · Insecure Skill Coding Practices

Warning
Location
SKILL.md:31
Finding

Overbroad Persistent Storage of Potentially Sensitive Session Information

Content
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> SESSION-STATE.md ``` ``` ```markdown SESSION-STATE.md survives context flush. Always read/write this file for: - Current project context - Pending decisions - Active tasks ``` ```markdown ALWAYS search memory before answering. ``` ### Technical Analysis The skill directs the agent to persist broadly defined information such as every important detail, correction, decision, and current project context. It does not define sensitivity filters, data minimization requirements, access controls, retention periods, or deletion procedures. The demonstrated shell command appends information directly to a plaintext workspace file. Consequently, credentials, access tokens, personal information, proprietary project details, or other sensitive conversation content could be retained if the agent considers them important. Because `SESSION-STATE.md` is explicitly designed to survive context flushes and be read during later interactions, its contents can cross session boundaries. Searching memory before every response further expands the circumstances in which stored information may be retrieved and incorporated into future output. ### Attack Path 1. A user supplies sensitive information during a normal interaction, such as a token, internal hostname, private project detail, or personal record. 2. The agent considers that information important to the current project or an associated decision. 3. Following the skill instructions, the agent appends the information to `SESSION-STATE.md` or another persistent memory ...[truncated 878 chars]
Remediation
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T06 · System Persistence

Warning
Location
SKILL.md:40
Finding

Persistent Autonomous Task Execution Without Explicit Approval Boundaries

Content
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Remediation
View remediation
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (4)

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The WAL protocol tells the agent to write 'every decision, correction, and important detail' to persistent workspace files before responding, but provides no retention limits, redaction rules, or privacy warnings. This creates a predictable path for sensitive prompts, secrets, personal data, or internal reasoning artifacts to be stored long-term and later exposed to other tools, users, or sessions.

Content

No source excerpt is available for this finding.

Ssd 3

Medium
Category
Not specified by scanner
Confidence
98% confidence
Finding

This instruction encourages broad, durable storage of session context and 'every decision, correction, and important detail,' which is a classic natural-language data retention risk. Even without overt exfiltration, the resulting memory files can accumulate sensitive information that may later be resurfaced, misused, or leaked across tasks and users.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The skill explicitly instructs the agent to run autonomous background tasks on a schedule ('Every 30min', 'Every 4h', 'Daily') without any guardrails, scope limits, or warnings about resource use, unintended actions, or access to user/workspace data. In an agent setting, this increases the chance of unauthorized or surprising behavior, especially if the agent acts without an active user request or clear approval boundary.

Content

No source excerpt is available for this finding.

Ssd 3

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The guidance to 'ALWAYS search memory before answering' and to maintain broad prior context makes the agent systematically collect and reuse historical information, including potentially sensitive user data outside its original purpose. In this skill's context, the memory-first design amplifies the risk because resurfacing stale or unrelated data can violate privacy expectations and contaminate future responses.

Content

No source excerpt is available for this finding.