Here’s a quick overview of AI-based open source tools that offer enhanced protection to networked systems against a range of cyber attacks.
Artificial intelligence (AI)-based applications using advanced chatbots are the norm today across industries like healthcare, retail and finance. The launch of ChatGPT by OpenAI has been followed by the release of many AI chatbots for multiple applications. Some of the major releases that followed ChatGPT include Gemini, Perplexity, Chatpdf, Bolt and Lovable. Numerous chatbots are currently under development and will soon be launched for multiple domains.
The global market size of AI was estimated at around US$ 200 billion in 2023 and is projected to grow at a CAGR of around 36% between 2023 and 2030.
AI in cybersecurity and network forensics
AI is not only useful for content writing but also for applications related to digital forensics and network management. It can be used for cyber forensics, network analytics and information security (Table 1).
| AI in cybersecurity and network forensics | AI-driven cyber deception |
| AI-driven cyber risk assessment | 5G and IoT security |
| AI-driven SOC (security operations centre) | AI-enhanced penetration testing |
| AI-powered endpoint detection and response (EDR) | AI-powered firewalls and IDS/IPS |
| AI-powered SIEM optimisation | Adversarial AI detection |
| Anomaly detection | Automated data privacy compliance |
| Automated incident response | Automated patch management |
| Botnet detection | Cloud security automation |
| Cyber risk scoring | DNS security |
| Dark web monitoring | Deception technology |
| Deepfake detection | Digital forensics |
| Encrypted traffic analysis | Forensics log analysis |
| Fraud detection | Identity and access management (IAM) |
| Insider threat detection | Malware analysis |
| Network traffic analysis | Phishing detection |
| Predictive threat intelligence | Quantum-safe cryptography |
| Ransomware protection | Secure DevOps (DevSecOps) |
| Security information and event management (SIEM) | Supply chain security |
| Threat detection and prevention | Threat hunting |
| User behaviour analytics (UBA) | Voice and chatbot security |
| Zero trust security | Self-learning AI for adaptive security |
Table 1: Key applications and use cases of AI in cybersecurity and network management
A few AI-based open source tools that are popular for cyber forensics and network analytics are listed below.
Threat intelligence and SIEM (security information and event management) tools
Wazuh (https://wazuh.com)
Wazuh is an open source monitoring tool integrated with AI-powered endpoint security, log analysis and evaluations. It uses its extended detection and response (XDR) as well as security information and event management (SIEM) capabilities to offer a unified platform for diversified protection.
Its endpoint security features include malware detection, configuration assessment, and file integrity monitoring. Regulatory compliance, incident response and IT hygiene make up its security operations. It also offers log data analysis, threat hunting, and vulnerability detection. Cloud security features include posture management, container security and workload protection.
Wazuh integrates comprehensive security mechanisms for multiple endpoints and digital infrastructure and can be used for high performance security and privacy-based applications.
MISP (https://www.misp-project.org/)
MISP is a high-performance platform for threat intelligence, analytics and evaluations using AI for detection and correlation of cyber threats.
It is used in a range of digital forensics-based applications for storage, sharing and collaborating on malware and cyber security-based operations. It works on the analytics and prevention of cyber frauds, threats, and attacks.
Network traffic analysis and intrusion detection tools
Zeek (zeek.org/)
Zeek is an AI integrated traffic analysis and network monitoring tool. The platform is used for analytics and prediction of malware and suspicious traffic in the network and digital infrastructure.
Snort (snort.org/)
This is an intrusion detection system (IDS) for detecting network threats. AI based models can use it for network management and analytics.
Suricata (suricata.io/)
This open source IDS/IPS tool has threat detection features, and integrates with AI for deep analytics of data and digital infrastructure.
Yara (virustotal.github.io/yara/)
Yara is focused on malware and classifies assaults associated with specific network signatures. Rule-based mechanisms can be programmed into this tool so that attacks can be evaluated effectively.
OpenVAS (openvas.org/)
OpenVAS is a multi-featured scanner for identifying different types of vulnerabilities and attacks in the network environment. It can evaluate and prioritise different protocols.
ClamAV (clamav.net/)
ClamAV is a high-performance platform used for the detection and deep evaluation of malware, viruses, Trojans and malicious threats. It can be used for scanning files and signature analytics.
Endpoint security and log monitoring tool
osquery (osquery.io/)
osquery is used for testing, analytics and endpoint security, and focuses on thread safety and memory leaks. It can be used to query systems to capture critical information, which is then analysed for forensics-based applications and predictive analytics.
These tools and frameworks can be used depending upon the security issue being addressed such as malware, Trojans, vulnerabilities, log files, and so on.
