Artificial intelligence or AI has become one of the most disruptive forces in cybersecurity, shaping how attacks are launched, detected, and mitigated.
At Dine with AlphaSec India, a cybersecurity event organized by Technophiles India, industry professionals came together to discuss how automation and machine learning are reshaping digital defense.
One of the key sessions — “Cybersecurity’s Double-Edged Sword: AI’s Role in Defense and Offense” — featured Kirill Bondarenko, APAC Sales Director at Axidian, alongside other regional experts. The discussion focused on how AI transforms both sides of the equation: empowering defenders while giving attackers new tools to exploit vulnerabilities.
AI in Cybersecurity — A Tool That Cuts Both Ways
The panel explored a difficult truth: the same technology that strengthens defense can also accelerate attacks.
AI-driven automation enables faster detection and response, but it also fuels more sophisticated threats — from adaptive malware to realistic phishing and deepfakes.
India’s security community is now addressing that balance head-on. As enterprises adopt AI to scale security operations, they face new risks in governance, transparency, and bias.
Panelists agreed that AI should extend human capabilities, not replace them and that the key lies in thoughtful implementation.
Kirill noted that AI empowers human capability — accelerating detection and freeing specialists to focus on complex, strategic work.
When applied thoughtfully, it can handle repetitive, time-consuming tasks, allowing specialists to focus on strategic analysis, risk assessment, and incident response.
He explained how AI-driven tools can help in three ways. Let’s break them down.
AI as an Assistant to Cybersecurity Officers
In this role, AI helps monitor and interpret user activity, detect anomalies, and prevent potential incidents before they escalate. The system continuously learns from normal patterns of behavior, enabling it to distinguish between routine actions and suspicious activity.
Core Detection Methods
1. User behavior analysis
AI identifies deviations from typical user actions.
Example: A member of the technical staff suddenly attempts to access financial data. Even if that access is formally allowed, the AI system flags the event and immediately triggers a response, blocking the session.
2. Command syntax analysis
AI evaluates the meaning of executed commands, identifying potentially harmful or suspicious operations — such as privilege escalation, configuration modification, or data exfiltration attempts.
3. Screen content analysis
This method “sees” what’s on a user’s screen in real time, detecting malicious pop-ups, fake banking portals, or unauthorized content that might indicate a phishing attempt or compromised session.
Key Benefits
- Accelerated detection and response: AI reduces response time by 40–60%, helping teams act before damage occurs.
- High data processing speed: AI engines can process millions of log entries per second, generating structured insights on the SIEM layer. Analysts spend less time on noise and more time on genuine threats.
2. AI as an Assistant to System Administrators
Beyond threat detection, AI can streamline identity and access management — an area often plagued by human error and administrative fatigue.
AI-driven access governance tools automatically assign or revoke access rights based on user roles, context, and activity patterns. This not only ensures compliance but also minimizes the risk of misconfigurations and privilege misuse.
Impact on Operations
For large enterprises with more than 1,000 employees, automation can:
- Cut administrative workload by 50%
- Reduce access configuration errors by up to 70%
This translates into a more secure, efficient environment where permissions are accurate, timely, and fully auditable.
3. AI in Action: Faster Threat Detection with Real Data
AI-driven security systems outperform traditional rule-based tools by combining behavioral, syntactic, and visual analysis.
Real-World Use Cases
- Behavioral anomaly detection: A manager attempts to export sensitive data at 3 AM (unusual time for such service) — AI immediately alerts the SOC team.
- Command-level prevention: When malicious scripts attempt to escalate privileges, AI blocks 99% of such malware in real time — even when attackers disguise commands.
- Visual threat recognition: The system detects a fake login page and warns the user before credentials are compromised.
- before credentials are compromised.
According to the IBM Cost of a Data Breach Report 2023, Extensive security AI and automation reduced the time to identify and contain a breach by more than 100 days.
AI doesn’t replace cybersecurity specialists — it can amplify their capabilities. By combining user behavior analysis, command syntax analysis, and screen content monitoring, security teams can gain a comprehensive, proactive defense layer.
