CoreSentrix Governance Deck

AI Risk Watch

A curated overview of incidents, failures, and governance challenges emerging across today’s AI landscape.
These examples highlight the increasing need for clear oversight, verification pathways, and human-centered governance structures.

This page aggregates publicly reported events from trusted sources.
It does not describe CoreSentrix internal systems, methods, or implementation details

Live Feed: AI Incidents & Systemic Risks

(This section aggregates publicly reported events. The feed updates automatically.) 

1. AI Safety Incidents

• Stanford AI Incident Database (RSS)
  
  

• MIT AI Policy & Safety News
  
  

• AI Village / DEFCON Responsible Disclosure Feed
  
  

2. Model Failures & Jailbreak Escapes

• Leading AI research blogs
  
  

• Security advisories on prompt manipulation
  
  

• Public jailbreak reports from reputable analysts
  
  

3. Deepfake Fraud & Media Integrity Risks

• Election-related deepfake alerts
  
  

• Identity theft / voice cloning incidents
  
  

• Verified media analysis feeds
  
  

4. Data Exposure & System Misuse

• Government cybersecurity advisories (CISA/NIST)
  
  

• Enterprise AI misuse case reporting
  
  

• Industry leak, breach, and misuse summaries
  
  

5. Automation Errors & Autonomous Agent Failures

• Reports on uncontrolled agent behavior
  
  

• Browser automation misfires
  
  

• AI toolchain execution errors
  
  

Why Track These Events?

As AI systems grow more powerful and more autonomous, failure conditions can spread across platforms, models, and workflows.
Tracking these incidents helps highlight the real-world environments where governance structures, oversight boundaries, and accountability pathways become essential.

This page does not analyze or interpret the incidents.
It simply aggregates publicly available reporting to support awareness and informed discussion.

Key Categories We Monitor

AI Jailbreaks & Boundary Failures

Publicly reported examples of AI systems producing content or actions outside approved guardrails.

Autonomous Workflow Errors

Incidents involving automated or agent-based systems performing unintended tasks or navigating unsafe pathways.

Data Exposure & Exfiltration Cases

Events where AI-driven outputs or workflows have led to unauthorized data release or leakage.

Deepfake & Media Integrity Incidents

Emerging cases of synthetic identity misuse, misinformation, and content manipulation.

System Instability & Drift

Observations of unexpected model behavior, degraded alignment, or unexplained output shifts.

Note:
This site presents real-world reporting without describing any CoreSentrix mechanisms or providing technical opinions.

How This Relates to Our Work

The governance concepts in the CoreSentrix portfolio were developed in response to the growing need for external oversight structures in environments where AI systems interact with decision pipelines, automation tools, and public-facing platforms.

This page illustrates part of the broader landscape in which these governance concepts may one day be applied.
No implementation details or system behavior explanations are shared.

Sources

All incident information originates from public reporting.
CoreSentrix does not evaluate, modify, or verify source content.

Inquiries

To request review of the CoreSentrix intellectual property portfolio:

📧 larry@coresentrix.com