Security audit

ddgs (DuckDuckGo Search)

Security checks for vulnerabilities and agentic risk

Overview

This is a straightforward DDGS web search helper; the main caveats are external search-query sharing and unpinned Python package installation.

Install in an isolated virtual environment, prefer a reviewed pinned version of `ddgs`, avoid the generic pip upgrade unless needed, and do not search for secrets, private identifiers, or internal-only information unless you are comfortable sending those terms to external search services.

A.I.G

Vulnerability Patterns

Insecure DependenciesIntroduces malicious components through unsafe dependency sources
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)

T08 · Insecure Dependencies

Warning

Location: SKILL.md:14
Finding: Unpinned Third-Party Dependency Installation
Content: View full analysis
Remediation: View remediation

SkillSpector

Vulnerability Patterns

Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code

Findings (2)

Missing User Warnings

Medium

Category: Not specified by scanner
Confidence: 95% confidence
Finding: The skill is explicitly about performing live web searches through DDGS and multiple backend search providers, but it does not clearly warn that user queries are transmitted off-system to external network services. In an agent setting, users may provide sensitive prompts, terms, or identifiers, and silent transmission of those queries can cause privacy leakage or policy violations.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 76% confidence
Finding: The natural-language guidance presents locale-specific region codes such as 'cn-zh' and 'us-en', and the examples hard-code region values without stating that users may choose their own locale preferences. Because locale can affect language and regional behavior, the documentation should make clear that these are optional examples rather than imposed defaults.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.