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Ingesting AI Guardrail Metadata from Salesforce Agentforce, crewAI and Guardrails AI into Collibra AI Governance

Sunil Soares, Founder & CEO, YDC March 26, 2025

Building Inventory of AI Guardrails to Support Marketing Brand

In a previous blog, I discussed the importance of having a consistent inventory of AI guardrails integrated with the AI use case registry. An AI leader mentioned this recently, “We are building a number of AI assistants and chatbots. We need a single inventory of AI guardrails that promote our global brand and drive a consistent marketing message.” Building a single inventory of AI guardrails is the first step to ensuring that AI agents support a global marketing message.

 

Ingestion of Guardrail Metadata from Salesforce Agentforce into Collibra AI Governance

As shown in the aforementioned blog, here is the JSON representation of agentic and guardrail metadata extracted from Salesforce Agentforce. The AI agent is the Support Assistant (company name is illustrative only) and the AI Guardrail is the Agentforce topic.


This metadata is ingested into Collibra AI Governance with the Support Assistant AI agent linked to the Agentforce Competitors Check AI guardrail object.


The Agentforce Competitors Check is mapped to the YDC AI Governance Control 10.6.15 – Avoid Competitor Mentions (YDC has a detailed inventory of 100+ AI Governance Controls).


Collibra also displays the traceability from the AI Use Case to the AI Guardrail and the AI Governance Control.

Ingestion of Guardrail Metadata from crewAI and Guardrails AI into Collibra AI Governance

crewAI is an agentic AI platform to build apps such as an Enterprise Content Marketing agent.


In an earlier blog, I discussed the integration between Collibra and the crewAI agentic AI platform. We used a third-party tool from Guardrails AI to add support for Personally Identifiable Information (PII) Detection. The Content Marketing Agent from crewAI is linked to the PII Detection guardrail from Guardrails AI in Collibra AI Governance.


The PII Detection AI Guardrail is linked to the YDC AI Governance Control 10.6.7 – Avoid Privacy Violation and to the OWASP LLM06 – Sensitive Information Disclosure AI Risk in Collibra (OWASP has since updated their Top 10 LLM for 2025).


The PII Detection guardrail is also linked to MITRE ATLAS AML.T0057 – LLM Data Leakage Technique.


Collibra also displays the traceability from the AI Use Case to the AI Guardrail and to OWASP, MITRE ATLAS and the AI Governance Control.

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Fairness & Accessibility

Component

Component ID: 5.0

Mitigate bias and manage AI accessibility.

List of Controls:

  • Bias
  • Accessibility
Mitigate Bias
Control
View Details
ID: 5.1

Ensure that AI systems are fair and manage harmful bias.
Component
Sub-Control
Regulation
  
Source
Address Fairness and Accessibility EU AI Act -Article 10(2)(f)(g) – Data and Data Governance (“Examination of Possible Biases”)

Vendors

Detect Data Poisoning Attacks
Control

View Details

ID: 10.4.1

Data poisoning involves the deliberate and malicious contamination of data to compromise the performance of AI and machine learning systems.

Component
Control
Regulation
Source
10. Improve Security10.4 Avoid Data and Model Poisoning AttacksEU AI Act: Article 15 – Accuracy, Robustness and Cybersecurity 

Vendors

Improve Security
Component

Component ID: 10

Address emerging attack vectors impacting availability, integrity, abuse, and privacy.  

List of Controls:

  • Prevent Direct Prompt Injection Including Jailbreak
  • Avoid Indirect Prompt Injection
  • Avoid Availability Poisoning
    • Manage Increased Computation Attack
    • Detect Denial of Service (DoS) Attacks
    • Prevent Energy-Latency Attacks
  • Avoid Data and Model Poisoning Attacks
    • Detect Data Poisoning Attacks
    • Avoid Targeted Poisoning Attacks
    • Avoid Backdoor Poisoning Attacks
    • Prevent Model Poisoning Attacks
  • Support Data and Model Privacy
    • Prevent Data Reconstruction Attacks
    • Prevent Membership Inference Attacks
    • Avoid Data Extraction Attacks
    • Avoid Model Extraction Attacks
    • Prevent Property Inference Attacks
    • Prevent Prompt Extraction Attacks
  • Manage Abuse Violations
    • Detect White-Box Evasion Attacks
    • Detect Black-Box Evasion Attacks
    • Mitigate Transferability of Attacks
  • Misuse of AI Agents
    • Prevent AI-Powered Spear-Phishing at Scale
    • Prevent AI-Assisted Software Vulnerability Discovery
    • Prevent Malicious Code Generation
    • Identify Harmful Content Generation at Scale
    • Detect Non-Consensual Content
    • Detect Fraudulent Services
    • Prevent Delegation of Decision-Making Authority to Malicious Actors

Identify Executive Sponsor

View Details

ID : 1.1 

Appoint an executive who will be accountable for the overall success of the program.

ComponentRegulationVendors
1. Establish Accountability for AIEU AI Act 
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