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A new era of cyber-threat

From silent and stealthy APTs, to fast-moving and destructive ransomware, cyber-attacks are outsmarting and outpacing defenders.

Security teams often struggle to differentiate subtle threats from normal business activity, relying on outdated tools incapable of keeping up with today’s attacks.

Stuck in the past

Traditional security tools widely in use today suffer from critical setbacks in three distinct areas.

Retrospective
Legacy tools react to attacks and only detect techniques they have seen before
Siloed
Cloud, email, network, endpoint and OT security has developed independently
Outpaced
The industry has a history of relying on humans to respond to machine-speed threats

Self-Learning AI: A unique approach

Reliance on traditional, legacy-based solutions is no longer adequate, and organizations are increasingly turning to Self-Learning AI to detect and autonomously respond to novel attacks.

The technology works by building an evolving understanding of your organization from scratch, allowing it to detect subtle outliers indicative of a threat in real time.

The following key trends in cyber-criminal activity threats have been observed across Darktrace’s customer base of over 5,500 organizations in 2021. The threat vectors are selected based on frequency of attacks, likelihood of success, and extent of financial and operational damage in the case of detonation.

of cyber security professionals believe AI augmentation is necessary for cyber defense.
Rising ransomware
With attackers turning to ‘double extortion’ ransomware that exfiltrates data before encryption, and increasingly targeting OT systems and critical infrastructure, this threat vector has made headlines again and again in the last twelve months.

Neutralizing zero-day ransomware with AI

Stealthy Advanced Persistent Threats
Often backed by nation-states, Advanced Persistent Threats can lay low inside digital systems for months, blending in with regular business activity to remain undetected.

How AI caught APT41 weeks before attribution

Increasing cloud-based attacks
With the wide-scale move to remote working and reliance on cloud collaboration platforms, attackers are targeting identities over devices – from spear phishing to account takeover.

Two cloud application attacks stopped by AI

Increase in ‘zero-days’
Attackers are updating their attack infrastructure faster than ever before, knowing that novel attacks evade the historical deny-lists relied on by email gateways, anti-virus, and traditional endpoint solutions.

Hafnium attacks stopped three months before attribution

AI-powered attacks
Last year, the World Economic Forum warned that the “first generation of AI-enabled offensive tools is emerging”, and will increase the speed, scale, sophistication, and stealth of cyber-criminal campaigns.

Learn more

Each trend is analyzed in detail by looking at a real-world threat discovered by AI in a customer environment. In every case, the threat in question slipped under the radar of the traditional security tools in place. By uncovering how Self-Learning AI was able to detect and remediate the threat based on off a series of subtle anomalies, the advantages of a self-learning, autonomous approach to cyber security is exemplified.

To buy back time for security teams, Self-Learning AI additionally carries out automated investigations that reduce time to triage by up to 92%. Combining expert analyst intuition with the speed and scalability of AI, this technology, called Cyber AI Analyst, connects the dots between disparate signs of attack...

Download the report below to continue reading

2021 Cyber-Threat Landscape: A New Era of Attack

Cyber-attacks are getting faster, stealthier, more sophisticated. Discover five key attack trends, and how to stay ahead of them with Self-Learning AI.

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