Dialogflow Cx Advanced

• Outcome: Pass
• Latest audit: Sep 11, 2026 · 1:49 AM UTC
• Version: 1.0.0

Overview

This skill provides disclosed Dialogflow CX management examples and a small read-only helper script, with credential and dependency hygiene caveats but no hidden or destructive behavior.

Before installing or using this skill, use a least-privilege Google Cloud identity, avoid pasting tokens or service-account JSON into shared transcripts, review any webhook destination because it can receive conversation/session data, and install Python dependencies in an isolated environment with pinned versions where possible.

A.I.G

Vulnerability Patterns

• Insecure Dependencies: Introduces malicious components through unsafe dependency sources
• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• Agent Memory Poisoning: Writes attacker-controlled rules into memory that affect later sessions
• Remote Payload Retrieval and Execution: Fetches external code whose behavior can change after review
• Embedded Malicious Code: Ships malicious scripts inside the skill and executes them locally

Findings (1)

T08 · Insecure Dependencies

Warning

• Location: scripts/advanced.py:10

Finding

Unpinned Third-Party Dependencies Create Supply-Chain Risk

Content

View full analysis

Vulnerability Details

File Location: scripts/advanced.py:10-15 and scripts/advanced.py:23-27
Vulnerability Type: Unpinned third-party dependencies
Risk Level: Medium

Vulnerable code:

python

Requires:
    - google-cloud-dialogflow-cx
    - google-auth

Install:
    pip install google-cloud-dialogflow-cx google-auth

python

except ImportError:
    print("Error: google-cloud-dialogflow-cx not installed")
    print("Run: pip install google-cloud-dialogflow-cx google-auth")
    sys.exit(1)

Technical Analysis

The project instructs users to install google-cloud-dialogflow-cx and google-auth without exact version constraints or package integrity hashes. Consequently, pip resolves whichever package versions and transitive dependencies are available from the configured package index at installation time. The effective executable dependency set can therefore change after this skill has been reviewed.

This does not establish that the named packages are currently malicious. However, if a future release, transitive dependency, configured package index, or dependency resolution path is compromised, installation or import of the resolved code could execute attacker-controlled Python under the privileges of the user running the skill. The absence of a lock file and hashes also prevents reliable verification that users install the same dependency artifacts that were security-reviewed and tested.

Attack Path

1. An attacker compromises a future dependency release, one of its transitive dependencies, or a package index used by the victim.
2. A user runs the recommended command: pip install google-cloud-dialogflow-cx google-auth.
3. Because no versions or hashes are specified, pip resolves and installs the attacker-controlled or compromised artifact.
4. Malicious code can run during package installation or when advanced.py imports the installed p ...[truncated 686 chars]

Remediation

View remediation

Remediation Suggestions

1. Pin every direct dependency to an exact, reviewed version rather than installing an unconstrained latest release.

2. Generate and commit a dependency lock file that captures all transitive dependency versions.

3. Record and enforce cryptographic hashes for downloaded artifacts, such as through a hash-locked requirements.txt installed with pip --require-hashes.

4. Replace the runtime error message with installation instructions that reference the reviewed lock file, for example:

   bash

   python -m pip install --require-hashes -r requirements.txt
   

5. Obtain packages only from a trusted, explicitly configured index and consider using an internally mirrored repository containing approved artifacts.

6. Automate dependency vulnerability scanning and controlled update review. Regenerate hashes and rerun security tests whenever dependencies are upgraded.

7. Run the CLI with least-privilege Google credentials and in an isolated virtual environment to reduce the scope of a dependency compromise.

SkillSpector

Vulnerability Patterns

• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• MCP Tool Poisoning: Hidden Instructions, Unicode Deception, Parameter Description Injection
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access
• Supply Chain: Unpinned Dependencies, External Script Fetching, Obfuscated Code

Findings (5)

Tp4

High

• Category: MCP Tool Poisoning
• Confidence: 91% confidence

Finding

The description overstates the skill's capabilities. The code only supports two read-only operations: listing environments and listing webhooks for a Dialogflow CX agent. It does not perform broader management actions, and it does not implement deployment management at all. While it does use the v3beta1 Dialogflow CX interface, it does so through the Python client library rather than directly via REST API. This is a material description-to-behavior mismatch.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 89% confidence

Finding

The skill instructs users to obtain and use bearer tokens and service-account credentials but does not include safeguards for handling secrets, such as avoiding shell history leaks, restricting credential scope, or preventing accidental logging/sharing. In an agent context, this increases the risk that sensitive cloud credentials are exposed to other tools, transcripts, or operators and then used to access Dialogflow or broader Google Cloud resources.

Content

No source excerpt is available for this finding.

External Transmission

Medium

• Category: Data Exfiltration
• Confidence: 60% confidence

Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 43)May include surrounding context.

List Environments

bash

curl -X GET \
  "https://dialogflow.googleapis.com/v3beta1/projects/${PROJECT_ID}/locations/${LOCATION}/agents/${AGENT_ID}/environments" \
  -H "Authorization: Bearer ${TOKEN}"

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 92% confidence

Finding

The reference includes inline webhook credentials and demonstrates sending session identifiers, parameters, and user text to an external endpoint without any warning about secret management, data minimization, or privacy handling. In an API reference for deployment and webhook configuration, readers may copy these patterns directly, leading to hard-coded secrets, unnecessary exposure of conversational data, and insecure downstream integrations.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

• Category: Not specified by scanner
• Confidence: 78% confidence

Finding

The natural-language example fixes the request locale to "en" with no note that other language codes may be used or that English is only illustrative. This can be read as enforcing a specific language without user opt-in or documented justification.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.