Loading story…
Google removed Google Signals from Analytics in June, eliminating a business-level setting that had prevented visitor activity from being shared with Google Ads. The change coincided with reported deterioration in consent compliance: U.S. sites ignoring opt-out signals increased from 81% to 87%, while European sites tracking users after cookie rejection rose from 52% to 56%.
Agentic AI compounds these governance gaps by executing rapid, multi-step actions across systems using delegated credentials. Organizations need continuous assurance over delegated permissions, explicit inheritance and boundary controls, rapid revocation mechanisms, and end-to-end provenance that connects a user request to every agent action; weak governance may also contribute to project failure, with Gartner predicting that more than 40% of agentic-AI projects will be canceled by the end of 2027.
Track how attackers are adapting to this technology.
3 events from the most recent confirmed update back to the earliest known activity.
Google launched Google Signals shortly after the GDPR. The feature allowed businesses to prevent visitor-activity data from being shared with Google's advertising network.
The reported share of U.S. websites ignoring opt-out signals rose from 81% to 87%, while European websites tracking after cookie rejection rose from 52% to 56%.
Google disabled Google Signals from its Analytics platform, removing a business-level control over sharing visitor activity with Google Ads and leaving Consent Mode as the mechanism for honoring cookie-consent choices.
Vulnerabilities, threat actors, malware, products, organizations, and breaches Mallory has linked to this story.
Follow how adversaries are adapting to this technology, and where it touches your stack today.
2 references tracked. Mallory keeps watching after this page renders.
Map indicators from this story to your assets and identify affected systems in minutes.
Every observed campaign, victim, and pivot linked to actors named in this story.
Malware, exploits, and IOCs connected to the activity described here.
YARA, Sigma, and Snort rules deployed to your SIEM as soon as they’re published.
Get matching new stories delivered to your team as they break — not the next morning.
Ask questions about this story and take action on the answers.
Other stories Mallory is tracking that overlap on entities, sources, or topic labels.
Enterprise adoption of AI agents is rapidly expanding the number of non-human identities inside corporate environments, with organizations increasingly running mixed stacks of coding assistants, writing tools, enterprise search, and agentic systems rather than relying on a single provider. Reporting based on Okta sign-on data from more than 20,000 organizations says each added AI platform brings more logins, secrets, tokens, service accounts, and permissions, while many companies still authorize agents with static API keys, OAuth apps, shared human accounts, or other weakly governed credentials that reduce auditability and increase the risk of over-permissioned access and orphaned accounts. Security reporting and industry data indicate that those governance gaps are already translating into higher exposure. The articles cite the `UNC6395` campaign, in which attackers allegedly abused a trusted OAuth token linked to Salesloft's Drift chat integration to pivot through Salesforce environments and obtain additional secrets including AWS credentials and Snowflake tokens, showing how machine identities can be exploited without a software flaw. A 2026 identity security report also found a 43% breach rate among organizations reporting AI-driven identity growth, versus 11% where AI had not significantly expanded identity counts, prompting calls for continuous inventory, clear ownership, least-privilege controls, lifecycle management, audit logging, and Zero Trust enforcement for AI agents and other machine identities.
Aug 20, 2026
Research commissioned by Cequence Security found that **65%** of 202 enterprise technology and security leaders have seen AI agents act outside their intended roles, and **29%** reported measurable business impact. Although **94%** of respondents believe their agents have no unnecessary access, only **33%** said agents are provisioned according to least-privilege principles, exposing a substantial gap between perceived and actual access governance. Organizations reported limited ability to authorize agent actions in real time, automatically detect and contain improper activity, or produce complete 30-day agent audit trails. Unmanaged non-human identities, incomplete agent inventories, unrestricted connections to external tools or data, and credentials left behind after paused AI pilots compound the risk. The report recommends treating agents as governed non-human identities, with runtime authorization, continuous monitoring, auditable activity records, automated containment, human approval for high-risk actions, and decommissioning processes that revoke credentials and permissions.
Sep 2, 2026
Enterprise adoption of task-specific AI agents is accelerating, with Gartner forecasting that **40% of enterprise applications** will include them by 2026, up from less than 5% in 2025. That growth is colliding with mounting security concerns over how autonomous agents are authorized, monitored, and constrained inside production environments. A widely discussed `r/sysadmin` post described a coworker granting Anthropic's Claude elevated SSH access to a virtualization host for routine administration, prompting warnings that external AI systems should not receive autonomous access to critical infrastructure without strict human review, change control, and narrowly scoped permissions. Those concerns have been sharpened by reported agent-related failures at major technology companies. SC Media cited a December 2025 incident in which Amazon's AWS coding agent **Kiro** inherited an engineer's elevated privileges and deleted then recreated a production environment, causing **13 hours of downtime**. It also described a March 2026 **Sev-1** incident at Meta in which an internal AI agent posted unapproved technical guidance that another engineer followed, exposing sensitive company and user data to unauthorized employees for nearly two hours. Security experts are increasingly calling for AI agents to receive distinct identities, auditable actions, and **just-in-time, least-privilege access** rather than broad inherited permissions or prompt-based guardrails.
Aug 3, 2026