Information Security

Securing-Agentic-AI-KrishnaG-CEO

Agentic AI Systems: The Rise of Over-Autonomous Security Risks

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Artificial Intelligence (AI) is no longer just a tool—it’s becoming a decision-maker. With the emergence of Agentic AI Systems—AI with the ability to independently plan, act, and adapt across complex tasks—organisations are entering uncharted territory. While this autonomy promises operational efficiency, it also introduces over-autonomous risks that challenge traditional cybersecurity protocols.
For C-Suite executives and penetration testers alike, understanding the evolution of AI from a predictive model to a proactive actor is no longer optional—it’s imperative. The very qualities that make agentic systems powerful—initiative, goal-seeking behaviour, and environmental awareness—also make them vulnerable to sophisticated threats and capable of causing unintentional damage.

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The Dark Web Economy: How Hackers Monetise Your Breach

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In an age of relentless digital transformation, your organisation’s data is currency — and hackers are the brokers. Beneath the surface of the internet lies a thriving, unregulated marketplace known as the Dark Web — a parallel economy where breached, stolen credentials, intellectual property, zero-day exploits, and malware-as-a-service offerings change hands like commodities.

The Dark Web is a portion of the internet that is purposefully hidden and inaccessible via standard web browsers. It requires anonymising tools such as Tor or I2P to access, and it hosts forums, marketplaces, and communication channels used for everything from whistleblowing to cybercrime.

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Information Security in the AI Era: Evolve Faster Than the Threats or Stay Behind

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In the corporate boardrooms and security operation centres of the 2020s, a new battlefront has emerged—cybersecurity in the AI era. The transformation is not subtle. Artificial Intelligence (AI) is no longer ahead of its time aspiration but a present-day force—amplifying threats and simultaneously offering powerful countermeasures. The question for today’s leadership isn’t whether AI will affect cybersecurity—it already has. The pressing challenge is: how quickly can your organisation evolve to match or outpace AI-enhanced adversaries?

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Defending Against Deepfake-Enabled Cyberattacks: Four Cost-Effective Strategies for C-Suite Leaders

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The rapid advancement of deepfake technology has transformed the cybersecurity threat landscape, particularly for C-level executives. Deepfake-enabled cyberattacks exploit artificial intelligence (AI) to create highly convincing fake videos, audio recordings, and images. These attacks are not merely theoretical; they are being actively used to defraud organisations, manipulate financial transactions, and compromise sensitive information.
For C-suite executives, the implications of deepfake threats are severe. Attackers can impersonate senior leadership to authorise fraudulent wire transfers, extract confidential data, or even manipulate corporate decision-making. Given the high stakes, it is critical for organisations to implement effective countermeasures.

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LLM10:2025 – Unbounded Consumption in LLM Applications: Business Risk, ROI, and Strategic Mitigation

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At its core, Unbounded Consumption refers to an LLM application’s failure to impose constraints on inference usage—resulting in an open door for resource abuse. Unlike traditional software vulnerabilities that might involve code injection or data leakage, Unbounded Consumption exploits the operational behaviour of the model itself—by coercing it into performing an excessive number of inferences.