AI moves fast. Stay in the know.
OpenAI’s ChatGPT Session Controls Improve Visibility, But Governance Gaps Remain
A recent update to ChatGPT introduced new session controls that give users and administrators better visibility into active logins across devices. While this improves account-level security, the larger governance challenge remains unresolved: AI systems are constantly evolving, and businesses may not always know when model behavior, outputs, or risk exposure changes. For companies adopting GenAI, the issue is no longer just who is logged in, but whether AI usage, model updates, and sensitive data interactions are being continuously monitored.
Source: InfoWorld
What to know:
- OpenAI’s new Active Sessions feature allows users to review browser and app sessions across ChatGPT, Codex, and the API Platform.
- The feature provides visibility into session details such as device, browser, approximate location, sign-in time, trusted device status, and current session activity.
- Users can log out of individual sessions or end sessions across devices, helping reduce the risk of unauthorized access going unnoticed.
- The update strengthens account visibility, but it does not fully address broader enterprise AI governance concerns.
- A key concern is that frequent AI model updates can change behavior after security, compliance, or business validation checks have already been completed.
- Businesses need continuous AI risk reassessment, usage monitoring, vendor change tracking, and governance controls beyond basic access visibility.
Why it matters:
For mid-sized businesses adopting GenAI, stronger ChatGPT session visibility is useful, but it is not enough on its own. AI risk now extends beyond account access into how employees use AI, what data enters AI systems, how model behavior changes, and whether approved workflows remain compliant over time. Without continuous observability, businesses may miss risky prompts, sensitive data exposure, unauthorized usage, or governance gaps caused by changing AI capabilities. This reinforces the need for AI monitoring, data protection controls, model-change tracking, and ongoing risk assessment as part of every GenAI adoption strategy.
AI-Generated Threats Are Becoming More Operationalized By Cybercriminals
TechRadar Pro reported that cybercriminals are increasingly using AI to scale fraud, impersonation, and cyberattack workflows. Citing Flashpoint research, the article highlighted how threat actors are using AI for deepfake-based KYC bypass, synthetic video, voice cloning, fake documents, jailbreak methods, phishing scripts, and prompt workflows. The findings show that AI misuse is becoming more organized, making it harder for businesses to detect fraud, social engineering, and AI-enabled security threats.
Source: TechRadar Pro
What to know:
- Cybercriminals are using AI to create more convincing phishing, fraud, and impersonation campaigns.
- Flashpoint research found AI being used for deepfake-based KYC bypass, synthetic video, and voice cloning.
- Threat actors are also using AI to generate fake documents, phishing scripts, jailbreak methods, and prompt workflows.
- AI tools are making it easier to scale attack tactics that previously required more time, skill, or manual effort.
- The article highlights the need for defenders to understand how AI-enabled threats are evolving across real-world attack scenarios.
- Businesses face growing risks around fraud, identity misuse, social engineering, and AI-generated malicious content.
Why it matters:
For mid-sized businesses adopting GenAI, AI security risk is no longer limited to internal tool usage. Attackers are also using AI to make fraud, phishing, and impersonation more believable and harder to detect. This increases the need for AI security monitoring, employee awareness, governance controls, and stronger visibility into how AI-generated content may be used to target employees, customers, and business systems.
Protections that work in the background without blocking workflows or slowing teams down.
RequestSmall Language Models (SLMs) run directly in the browser or on local environments—nothing sensitive is ever sent to the cloud.
Generate PolicyOur platform is built to adapt—whether you're rolling out GenAI, scaling SaaS, or securing hybrid teams.
Read the case study


