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- Automation Overload: When Bots, Vendors & Data Lakes Go Bad
Automation Overload: When Bots, Vendors & Data Lakes Go Bad
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AI Jailbreaks: Prompt Injection as a Security Threat
Attackers are now using prompt injection to “jailbreak” enterprise AI tools—bypassing restrictions and extracting sensitive data. These attacks target customer service bots, AI copilots, and internal LLM interfaces.
Mitigation includes input sanitization, using guardrails like content filtering, and sandboxing high-risk AI interactions. Enterprises should log and monitor LLM activity like any privileged system.
Voice Biometrics Under Fire: Spoofing Gets Sophisticated
Voice authentication was once seen as secure. Now, AI-generated spoofing tools are bypassing voiceprint systems with high accuracy.
To protect access, pair voice ID with behavioral signals or multi-modal biometrics. Regularly re-enroll voice profiles and use liveness detection to ensure signals come from real humans, not recordings.
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The Risks of Hyperautomation: Bots Gone Rogue
Automation is great—until it runs unchecked. In 2025, many security incidents stem from misconfigured bots or RPA tools executing outdated logic with elevated privileges.
Audit RPA scripts regularly, limit bot access rights, and include bots in IAM frameworks. Treat them like users—because they can make just as many mistakes.
The New Target: MSPs and IT Outsourcing Vendors
Managed service providers (MSPs) are now prime targets—attack one vendor, breach dozens of clients. Threat actors exploit trust, shared access, and weak vendor hardening.
Mandate third-party security reviews, isolate vendor accounts, and use zero-trust policies even with “trusted” partners. The weakest vendor can take down your whole stack.
Data Lakes & Data Drains: Privacy Risks in Unstructured Storage
Data lakes offer massive storage—but often lack fine-grained access control. Sensitive files buried in unstructured formats can be accidentally exposed or scraped.
Deploy data classification and masking tools, control access by user role and location, and apply encryption by default. Just because it’s “big data” doesn’t mean it should be a big target.
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