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Security audit

Academic Deep Research

Security checks for vulnerabilities and agentic risk

Overview

This research skill is mostly purpose-aligned, but it should be reviewed because it can automatically use web research, parallel sub-agents, and persistent memory in ways that are not clearly scoped for users.

Review this skill before installing if your research topics may include confidential business plans, regulated data, personal information, or sensitive security context. Use it only when you are comfortable with platform web search/fetch, possible sub-agent task sharing, and memory lookup; ask the agent to avoid persistent memory and to show planned search queries before any outbound research.

Vulnerability Patterns
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
  • 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 (2)

T05 · Unauthorized Access and Privilege Escalation

Warning
Location
SKILL.md:431
Finding

Unnecessary Access to Persistent Agent Memory

Content
View full analysis

Vulnerability Details

File Location: SKILL.md, lines 431-442
Vulnerability Type: Least-privilege violation through cross-session memory access
Risk Level: Medium

Vulnerable Code Snippet

markdown
### Memory Search Integration

Before starting research, check for relevant prior knowledge:

→ memory_search(query="previous research on [topic]") → memory_get(path="memory/YYYY-MM-DD.md") [if relevant date found]

text

Use prior findings to:
- Avoid duplicate research
- Build on previous conclusions
- Identify how understanding has evolved
- Note persistent gaps from prior research

The associated tool declaration appears at SKILL.md:31:

markdown
| `memory_search` / `memory_get` | Cross-reference prior knowledge | Check MEMORY.md for related context |

Technical Analysis

The Skill instructs the agent to search and read persistent memory before conducting research. Access to cross-session memory is not necessary for the declared core functionality of performing literature reviews and web-based research. The instruction therefore exceeds the minimum privileges needed by the Skill.

Persistent memory may contain information from unrelated users, conversations, or prior tasks. The Skill does not require explicit consent before searching this data, define an allowed memory namespace, restrict which records may be opened, or prevent retrieved content from being incorporated into later tool calls.

This is a read-side privilege issue rather than memory poisoning: the reviewed Skill does not write attacker-controlled instructions into persistent memory. No direct malicious collection endpoint was found. Nevertheless, once private memory content enters the research context, it may influence generated search queries, spawned-agent tasks, or the final report.

Attack Path

  1. A user invokes the Skill for a research topic.
  2. The Skill automatically calls memory_search usi ...[truncated 1161 chars]
Remediation
View remediation

Remediation Suggestions

Remove memory_search and memory_get from the default research workflow. The declared research functionality can operate using user-approved inputs and public sources without persistent-memory access.

If cross-session continuity is retained as an optional feature:

  1. Require explicit, informed user consent before every memory search.
  2. Explain what memory namespace, date range, and subject will be searched.
  3. Restrict retrieval to records created for the same user and research project.
  4. Present matching record metadata before opening the record.
  5. Retrieve only the minimum required excerpt instead of an entire memory file.
  6. Treat retrieved memory as confidential by default.
  7. Prohibit inserting memory-derived content into web_search, web_fetch, or sessions_spawn calls without separate user approval.
  8. Add redaction controls for credentials, personal data, health information, proprietary material, and other sensitive content.
  9. Record auditable disclosures of which memory records were accessed and how they were used.

other

Note
Location
README.md:11
Finding

Misleading Offline Claim Despite Mandatory Network Research

Content
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Vulnerability Details

File Location: README.md, lines 11 and 77-82
Vulnerability Type: Misleading network-use and privacy representation
Risk Level: Low

Vulnerable Code Snippet

The README represents the Skill as offline-capable:

markdown
- ✅ **Works offline** — No third-party API keys required

The same README later defines network-dependent execution:

markdown
### Phase 3: Execution (Auto)
For each theme, two full cycles:
- `web_search` (count=20) for landscape
- Analysis and gap identification
- `web_fetch` on primary sources
- Synthesis and assumption challenging

The mandatory network behavior is also specified in SKILL.md:181-185:

markdown
1. **START:** `web_search` for landscape (count=20)
2. **ANALYZE:** Synthesize findings, identify patterns, note gaps
3. **DIVE:** `web_fetch` on primary sources for depth
4. **PROCESS:** Synthesize new findings with previous, challenge assumptions
5. **REPEAT:** Second cycle targeting identified gaps

Technical Analysis

The claim that the Skill “works offline” conflicts with the required use of web_search and web_fetch. Although the Skill does not require users to supply third-party API keys, the absence of user-managed credentials does not make the workflow offline.

Network research is legitimate and necessary for the declared purpose of investigating current public sources. The security concern is the inaccurate disclosure rather than the existence of network behavior itself. Search queries are derived from user-provided topics, constraints, industries, and source preferences. These values may reveal confidential research interests or organizational plans to the platform's search and fetch providers.

The reviewed files do not specify an attacker-controlled destination, transmit credentials, fetch executable code, or execute remote payloads. The risk arises because users may provide sensitive material wh ...[truncated 1415 chars]

Remediation
View remediation

Remediation Suggestions

Replace the offline claim with a precise network disclosure, such as: “Uses platform-provided web search and page retrieval tools; no user-supplied third-party API key is required.”

The Skill should also:

  1. Clearly disclose before execution that research queries and requested URLs will be sent through network services.
  2. Warn users not to include credentials, protected health information, trade secrets, or unnecessary personal data in research prompts.
  3. Show or summarize planned search queries during the existing research-plan approval checkpoint.
  4. Require separate confirmation before transmitting queries derived from confidential material.
  5. Minimize query contents by removing names and sensitive context that are unnecessary for source discovery.
  6. Document the platform services involved, their retention behavior, and applicable privacy boundaries where known.
  7. If offline capability is intended, implement a distinct offline mode that disables web_search, web_fetch, and other network-dependent tools and operates only on user-provided local material.
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Findings (7)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The README advertises very broad natural-language activation phrases such as asking for "deep research on..." or "exhaustive analysis of...", which can cause unintended invocation when a user is speaking generally rather than intentionally selecting this skill. In an agent ecosystem, overly generic triggers increase the chance of misrouting requests into a high-cost, autonomous research workflow that performs many searches and fetches, potentially causing unnecessary external access, cost, or disclosure of user intent to web tools.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The trigger examples are broad enough to match common requests like "Tell me everything about X" or generic "exhaustive analysis," which can cause the skill to activate when the user did not explicitly request heavyweight web research. In this skill, unintended activation is more concerning because it can initiate external web access, memory access, and parallel sub-agent spawning, increasing the chance of unnecessary data exposure, cost, and unexpected autonomous behavior.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The tool configuration enables web access, memory retrieval, and parallel sub-agent execution, but the skill description does not prominently warn users that their request may trigger external browsing and isolated sub-agents. This reduces informed consent and can lead users to disclose sensitive information or approve research without understanding that data may be sent to external sources or processed by multiple agent contexts.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
88% confidence
Finding

The workflow repeatedly instructs use of external web_search and web_fetch for healthcare, HIPAA, PHI, and security-related topics without any caution about sending sensitive organizational context, internal constraints, or regulated data to third-party services. In a research skill aimed at healthcare use cases, this omission can cause users or downstream agents to include confidential environment details in queries or fetch regulated content into external tooling, creating avoidable data exposure risk.

Content

No source excerpt is available for this finding.

Autonomous Decision Making

Medium
Category
Excessive Agency
Confidence
85% confidence
Finding

The 'Auto-Execute' phase encourages the skill to proceed with multi-step external research actions autonomously rather than requiring an approval checkpoint before tool use. In a context involving security-sensitive and healthcare-related research, autonomous execution increases the chance of unreviewed outbound queries, excessive data collection, and unintended transmission of sensitive context to external services.

Content

Scanner excerpt · example.md (reported line 76)May include surrounding context.

md
---

## Phase 3: Research Cycles (Auto-Execute)

### Theme 1: Market Landscape — Cycle 1

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The invocation guidance is overly broad because phrases like "deep research" or "exhaustive analysis" can plausibly appear in ordinary conversation rather than as a deliberate command. That increases the chance of accidental activation of a powerful workflow that performs multi-phase automated research, potentially causing unintended tool use, time consumption, and external data access.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The skill specifies a fully automated execution phase using web_search and web_fetch, but it does not clearly warn the user that external network access and third-party content retrieval will occur. This can undermine informed consent and create privacy, compliance, or expectation risks if the user did not realize their request would trigger outbound research activity.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.