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Vulnerability assessment and management

Computer Science (Cyber Security) (B.E./B.Tech) · Offensive and defensive security · free study notes for exams, placements and interviews

In short

Vulnerability assessment (VA) is the systematic discovery, classification and scoring of security weaknesses in hosts, applications, networks and configurations; vulnerability management (VM) is the continuous programme that prioritises, remediates, verifies and reports on them. It differs from penetration testing in that VA is broad, largely automated and non-exploitative, while a pen test is narrow, manual and proves exploitability. It matters because almost all mass breaches and ransomware in India exploit known, patchable flaws, and because CERT-In directions, RBI/SEBI/IRDAI cyber frameworks, ISO/IEC 27001:2022 and PCI DSS all mandate periodic VA. It is examined in university "Offensive and Defensive Security" / "Cyber Security Essentials" papers, and asked in every VAPT, SOC-analyst and GRC interview at TCS, Infosys, Wipro, HCLTech, Accenture, Deloitte, KPMG, Tata Elxsi, Qualys and Tenable partners in India.

Explained

Core definitions and the risk equation

Classification and standards ecosystem

Types of assessment and scanning techniques

The vulnerability management lifecycle

  1. Discover / inventory: build and continuously update the asset register with ownership, business criticality and data classification.
  2. Categorise and prioritise assets: crown-jewel systems (core banking, UPI switch, PII stores) get tighter scan frequency and SLAs.
  3. Scan / assess: scheduled authenticated scans plus continuous agent telemetry; define scope, credentials, bandwidth throttling and blackout windows.
  4. Validate and triage: remove false positives, confirm reachability and compensating controls, deduplicate findings per asset.
  5. Risk-rank: combine CVSS base, EPSS, KEV status, asset criticality and exposure (internet-facing?) into a single prioritised queue.
  6. Remediate: patch, upgrade, reconfigure, or - where patching is impossible - mitigate (WAF rule, segmentation, disable service) or formally accept the risk with sign-off and an expiry date.
  7. Verify: rescan to confirm closure; never close on a ticket comment alone.
  8. Report and improve: dashboards, trends, MTTR, SLA compliance, exception register; feed root causes back into hardening baselines and SDLC.
  9. Vulnerability management vs patch management: patching is one remediation action; VM is the whole risk-decision process, including findings that have no patch.

Tools, and VA versus penetration testing

Indian standards, law and practice

Key points

Formulas and examples

Risk = Threat × Vulnerability × Impact (qualitative model); residual risk = inherent risk − effect of controls
CVSS v3.1 Base Score: Exploitability = 8.22 × AV × AC × PR × UI; Impact(ISS) = 1 − [(1−C)(1−I)(1−A)]; for Scope Unchanged, Impact = 6.42 × ISS; Base = Roundup(min(Exploitability + Impact, 10)) when Impact > 0, else 0
Risk score (practical) = CVSS_base × EPSS × Asset_criticality_weight (dimensionless, used to rank a queue)
Remediation rate = vulnerabilities closed in period ÷ (vulnerabilities open at start + newly found in period) × 100 (%)
MTTR = Σ (date closed − date detected) ÷ number closed (days)
Vulnerability density = number of valid vulnerabilities ÷ number of assets (or ÷ KLOC for code)
False discovery rate (what VM reports loosely call "false positive rate") = FP ÷ (FP + TP) × 100 (%) = 1 − Precision; strictly, false positive rate = FP ÷ (FP + TN); Precision = TP ÷ (TP + FP); Recall = TP ÷ (TP + FN)
Window of exposure = date patched − date patch available (days)

Example 1 - CVSS v3.1 base score for an unauthenticated remote RCE. Vector: AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.

Example 2 - risk-based prioritisation of a 2,000-finding backlog.

CVECVSSEPSSAsset weight (internet-facing core = 5, internal = 2)Risk score
A9.80.8059.8 × 0.80 × 5 = 39.2
B9.80.0129.8 × 0.01 × 2 = 0.196
C6.50.6056.5 × 0.60 × 5 = 19.5
D7.50.0527.5 × 0.05 × 2 = 0.75

Order of work: A, C, D, B. Note that C (Medium severity) outranks B (Critical severity) - the point of risk-based VM. Patching A and C first removes the two highest-risk items while touching only 2 of 4 change tickets.

Example 3 - false positive rate and precision. A credentialed Nessus scan of 500 Linux servers reports 1,250 High/Critical findings. Manual validation confirms 1,000 real, 250 not real; a later pen test finds 50 real High issues the scan missed.

Example 4 - SLA compliance and MTTR. Twelve Critical vulnerabilities closed in a quarter; SLA = 15 days. Closure ages (days): 3, 5, 7, 8, 10, 12, 14, 15, 18, 22, 30, 36.

Example 5 - scan effort and window planning. A bank must scan 3,000 hosts. A single scanner engine handles 20 hosts in parallel, averaging 6 minutes per credentialed host.

AspectVulnerability assessmentPenetration testingRed teaming
GoalEnumerate and score weaknessesProve exploitability and impactTest detection and response end-to-end
Breadth vs depthBroad, shallowNarrow, deepObjective-driven
AutomationMostly automatedManual with tool supportManual, adversary-emulating
FrequencyContinuous / monthly / quarterlyAnnual or per releaseOccasional
OutputRanked finding listAttack chains and proofsCampaign narrative and gaps
Blue team awareYesUsually yesUsually no

Where it is used

Interview questions

Common mistakes

Related topics

Ethical hacking and penetration testing · Web application security (OWASP Top 10) · Security operations: SOC and SIEM · Threat intelligence and MITRE ATT&CK · Incident response and threat hunting · Security governance, risk and compliance (ISO 27001, PCI DSS)

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