Theoretically, AI agents can surf the web, access datasets through APIs, write and execute code, conduct online transactions, ...

Researchers have built a new tool that leverages both federated learning and blockchain as a bulwark against data poisoning.

Researchers have developed a novel attack that steals user data by injecting malicious prompts in images processed by AI ...

The rapid adoption of Large Language Models (LLMs) has reshaped the digital ecosystem, powering everything from customer ...

Security researchers continue to find new ways that AI can be used to target victims, such as including hidden text in images ...

Most organizations are unaware of how vulnerable their cloud systems have become. Gaps in preparation could cause serious ...

Data poisoning corrupts AI systems by teaching them with bad data. There’s no silver bullet to protect against it, but ...

Training data poisoning (LLM03) and model poisoning: Attackers corrupt training data by sneaking in tainted samples, planting hidden triggers. Later, an innocuous input can unleash malicious outputs.

Closing Thoughts Model supply-chain poisoning is a critical and under-addressed threat. The safest path is to see models not only as assets but also as potential attack vectors.

Trust is not something that emerges after successful deployment; it is the baseline upon which safe, secure and ethical AI ...

According to MarketsandMarkets™, the Generative AI Cybersecurity Market is slated to expand from USD 8.65 billion in 2025 to ...