Gartner

CTEM Without the Hype: Understanding Gartner's Continuous Threat Exposure Management Framework

The article explains the evolution of vulnerability management from basic scheduled scanning to risk-based approaches and finally to Continuous Threat Exposure Management (CTEM). It positions CTEM as a comprehensive program introduced by Gartner in 2022 that integrates asset management, EASM, CAASM, automated pentesting, and business-context prioritization. The five-stage cycle of Scoping, Discovery, Prioritization, Validation, and Mobilization is detailed with practical examples such as protecting customer databases in an e-commerce environment. Gartner predicts organizations prioritizing CTEM will suffer three times fewer breaches by 2026, though only 16% have reached operational maturity. The piece also covers common implementation pitfalls and the emergence of the first Magic Quadrant for Exposure Assessment Platforms featuring vendors like Tenable, Qualys, and Rapid7.

AI Reshapes Cybersecurity Jobs: Automation of Routine Tasks, Rising Demand for Architects and AI Defenders

The cognitive revolution driven by AI technologies is transforming the information security job market rather than eliminating it. Routine tasks such as alert triage, log analysis, and basic vulnerability prioritization are increasingly handled by language models and autonomous agents, shifting human roles toward setting boundaries, validating hypotheses, and assuming legal and financial responsibility. Surveys from ISC2 and analyses by Gartner highlight growing needs for senior architects, AppSec engineers, DevSecOps specialists, and experts protecting AI systems themselves. DARPA's AIxCC competition demonstrated both the promise and limitations of autonomous patching, with 37-45% of generated fixes containing hidden semantic errors. Russian market data from Positive Technologies and SuperJob shows 24-26% growth in vacancies focused on experienced professionals amid import substitution pressures. The profession is moving from mechanical execution to designing reliable architectures and overseeing automated defense loops through 2030.

Deepfakes Turn Job Interviews into Cyberattack Vectors Targeting IT Candidates and Recruiters

Deepfake technology and malicious test assignments are increasingly used during IT hiring processes to conduct industrial espionage or deploy malware. Attackers impersonate recruiters or candidates, sending infected GitHub repositories or npm packages that install backdoors stealing credentials and enabling remote access. Groups such as Lazarus and the dedicated Contagious Interview collective have run campaigns against chemical and IT firms, while individual cases like the Smello Python developer incident show how prepare scripts in package.json can trigger hidden payloads. Gartner predicts that by 2028 one in four job applicants could be fake, creating risks beyond bad hires including data theft and financial loss. Defenses include isolated virtual machines for test tasks, profile verification by companies like Socure, and interview techniques such as the GOTCHA movement challenges or corneal reflection probes developed by universities. Major firms including Cisco, McKinsey, and Google are returning to in-person interviews as a reliable countermeasure. The rapid evolution of deepfake quality tracked by Unit 42 means layered verification combining technical, procedural, and human checks is now essential.

Aligning AI Adoption Maturity with AI Security Using CMMI and Russian Regulatory Requirements

Organizations frequently operate at mismatched maturity levels between AI implementation and AI security controls, creating significant gaps that lead to incidents and regulatory violations. The analysis maps both dimensions onto the five-level CMMI scale, showing how adoption often outpaces protection and highlighting the risks of Shadow AI, uncontrolled agents, and non-compliance. Key frameworks including OWASP AIMA, Google SAIF, NIST AI RMF, and MITRE ATLAS are aligned to CMMI levels L1 through L5. Russian requirements under FSTEC Order No. 117, effective March 2026, introduce mandatory controls for trusted AI technologies, data handling, and statistical response validation that activate precisely at the L2-to-L3 transition. The article details predictable organizational states from denial to managed agentic systems and provides a practical matrix linking each CMMI level to minimum security requirements and specific Russian compliance anchors such as GOST R 56939-2024 and ISO/IEC 42001.