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Security audit

Intellectia Stock Forecast

Security checks for vulnerabilities and agentic risk

Overview

This skill is a disclosed stock-analysis API helper that sends ticker and prompt data to SkillBoss, with privacy considerations but no hidden or destructive behavior found.

Install only if you are comfortable sending stock tickers and financial-analysis questions to SkillBoss using your API key. Do not include account numbers, private portfolio details, proprietary trading strategies, or other confidential information in prompts.

SkillSpector

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 (8)

Missing User Warnings

Medium
Confidence
88% confidence
Finding
The skill clearly instructs the agent to send user-provided stock questions and prompts to a third-party API using an API key, but it does not prominently warn that request contents will leave the local environment and be processed by SkillBoss. This creates a privacy and data-governance risk because users may unknowingly transmit sensitive portfolio, strategy, or personal financial context to an external service.

External Transmission

Medium
Category
Data Exfiltration
Content
python3 - <<'PY'
import requests, os
SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
r = requests.post(
    "https://api.skillboss.com/v1/pilot",
    headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
    json={"type": "search", "inputs": {"query": "TSLA stock price forecast predictions 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035"}, "prefer": "balanced"},
Confidence
80% confidence
Finding
The Python example demonstrates sending externally supplied content and an authorization header to a remote API. While standard for an API client, this still represents a trust-boundary crossing and may expose confidential request content if users assume local-only processing.

External Transmission

Medium
Category
Data Exfiltration
Content
python3 - <<'PY'
import requests, os
SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
r = requests.post(
    "https://api.skillboss.com/v1/pilot",
    headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
    json={
Confidence
80% confidence
Finding
The second Python example transmits a natural-language investment question to a remote service for LLM processing. Because such prompts can contain rich contextual information, the external transmission risk is real even if no explicit secret exfiltration is present.

External Transmission

Medium
Category
Data Exfiltration
Content
python3 - <<'PY'
import requests, os
SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
r = requests.post(
    "https://api.skillboss.com/v1/pilot",
    headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
    json={"type": "search", "inputs": {"query": "TSLA stock price forecast predictions 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035"}, "prefer": "balanced"},
Confidence
80% confidence
Finding
The Python example demonstrates sending externally supplied content and an authorization header to a remote API. While standard for an API client, this still represents a trust-boundary crossing and may expose confidential request content if users assume local-only processing.

External Transmission

Medium
Category
Data Exfiltration
Content
python3 - <<'PY'
import requests, os
SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
r = requests.post(
    "https://api.skillboss.com/v1/pilot",
    headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
    json={
Confidence
80% confidence
Finding
The second Python example transmits a natural-language investment question to a remote service for LLM processing. Because such prompts can contain rich contextual information, the external transmission risk is real even if no explicit secret exfiltration is present.

External Transmission

Medium
Category
Data Exfiltration
Content
### Example (cURL)

```bash
curl -sS -X POST "https://api.skillboss.com/v1/pilot" \
  -H "Authorization: Bearer $SKILLBOSS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"type":"search","inputs":{"query":"TSLA stock price forecast predictions 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035"},"prefer":"balanced"}'
Confidence
79% confidence
Finding
This cURL command actively demonstrates an outbound POST containing a search query and bearer token. In the context of a skill that may be run by users or agents automatically, that is a real external data-sharing behavior and should be treated as security-relevant.

External Transmission

Medium
Category
Data Exfiltration
Content
### Example (cURL)

```bash
curl -sS -X POST "https://api.skillboss.com/v1/pilot" \
  -H "Authorization: Bearer $SKILLBOSS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"type":"search","inputs":{"query":"TSLA stock price forecast predictions 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035"},"prefer":"balanced"}'
Confidence
79% confidence
Finding
This cURL command actively demonstrates an outbound POST containing a search query and bearer token. In the context of a skill that may be run by users or agents automatically, that is a real external data-sharing behavior and should be treated as security-relevant.

External Transmission

Medium
Category
Data Exfiltration
Content
### Example (cURL)

```bash
curl -sS -X POST "https://api.skillboss.com/v1/pilot" \
  -H "Authorization: Bearer $SKILLBOSS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"type":"chat","inputs":{"messages":[{"role":"user","content":"Should I buy TSLA stock? Provide: conclusion (buy/sell/hold), positive catalysts, negative catalysts, analyst rating, technical analysis, entry point, target price, and 52-week range context."}]},"prefer":"balanced"}'
Confidence
80% confidence
Finding
The cURL chat example demonstrates sending a natural-language investment prompt to a third-party API. That introduces a genuine privacy risk because prompts may contain user-specific financial details, strategies, or other sensitive information.

Static analysis

No suspicious patterns detected.