A mid-sized company’s IT team is usually only a few people, yet every day thousands of log lines are generated by the firewall, servers, email and antivirus. No human can read them all. This is where AI comes in. On the other hand, attackers have access to the same tools and use them to attack faster and more convincingly. Understanding both edges of this sword is essential for making the right decisions.
AI in the defender’s hands
Many security products have used machine learning for years, and capabilities based on language models are now being added to them. Common uses:
- Detecting abnormal behavior: the system learns what normal behavior looks like for users and servers and reports deviations, such as an account signing in at an unusual hour or a large volume of data being sent out.
- Endpoint protection (EDR): instead of relying only on signatures of known malware, it detects and stops suspicious program behavior such as mass file encryption.
- Email filtering: detecting spoofed emails and malicious attachments based on content and sending patterns.
- Log analysis and alert prioritization: in SIEM systems, it groups related alerts and tells the analyst where to start.
- Helping the analyst: explaining an alert, summarizing an incident or suggesting investigation steps in plain language.
Limits of smart defense
- False positives: the system may flag legitimate behavior as suspicious, or the reverse, treat a quiet attack as normal.
- Dependence on good data: if logs aren’t collected or server clocks aren’t synchronized, no intelligence will help.
- Black box: it isn’t always clear why the system judged something dangerous.
- Cost and complexity: these products usually need licenses, hardware resources and an expert to tune them. Their capabilities and terms also differ between vendors and change constantly.
AI is no substitute for the basics. A company without security updates, two-factor authentication and an off-network backup won’t become secure by buying a smart product.
AI in the attacker’s hands
- More convincing fake emails and messages: flawless text tailored to the target, in any language and at large volume.
- Fast information gathering: summarizing public information about a company and its employees to plan an attack.
- Help writing malicious code and finding weaknesses: reputable services have restrictions, but attackers find other tools, and they now work faster.
- Voice and video impersonation: to deceive employees and request payments or information.
Attacks on AI tools themselves
If a company uses an AI assistant connected to email, documents or internal systems, it creates a new attack surface. In an attack called Prompt Injection, an attacker hides instructions in an email, web page or document so the assistant carries them out, for example sending information outside. For this reason, give these assistants only the minimum access they need, require human approval for sensitive actions such as sending or deleting, and log their activity.
Checklist
- The basics, including updates, two-factor authentication and an off-network backup, are in place.
- Logs from the firewall, servers and systems are collected and retained in one place.
- Before buying a smart security product, you have trialed it on your own network for a while.
- Someone is responsible for reviewing alerts, not just receiving them.
- AI assistants connected to systems have minimum access.
- Employees receive regular training on new kinds of deception.
AI doesn’t fully tip the security balance in favor of either side; the winner is whoever has strengthened the basics. ITPlus724 engineers can implement and review your company’s network and firewall security, log collection and secure backups.