Running

Software Development Lifecycle

Software Platforms

• Endpoint applications (self contained on device)
• Client/Server apps

Development Methodologies

Incorporate security at every stage

• Waterfall: rigid, linear, steps
• Spiral: iterative process
  • Begin / Dev & Test / Risk Assess / Determine Requirements / recycle
• Agile (continuous dev, short dev/release cycles); prioritise:
  • Individuals/interactions over processes/tools
  • Working Software over documentation
  • Customer collaboration over contracts
  • Respond to change over follow plan

Maturity Models

Standard benchmarks: CMMI (Capability Maturity Model Integration):

• Initial
• Managed
  • Reuse code, config management, project planning, QA, requirements management
• Defined
  • Documented practices, integrated project management, risk management, validation, etc
• Quantitatively Managed
  • Organisation process management, quantitative project management
• Optimising
  • Continuous process management, causal management and resolution

Current version used for software dev plus supply chain and others.

IDEAL model is an alternative:

• Initialising
• Diagnosing
• Establishing
• Action
• Learning

Change Management

• Request control
• Change control > through CAB, docs
• Release management > through QA against RFC
• Dev > Test > Staging > Production environments

Automation and DevOps

Build collaborative relationships Embrace automation Facilitate rapid releases Provide a stable operating environments

DevOps and Agile both seek continuous operation "interactions as code2 > eg script to change Base OS image to specific requirement > scalable, use of immutable servers, reduce errors, facilitate testing Facilitates security automation > "DevSecOps"

• Continuous validation
• Continuous integration
• Continuous delivery
• Continuous deployment
• Continuous monitoring

Software Quality Assurance

Code Review

Peer analysis Formal, FAGAN:

• Planning
• Overview > assign roles
• Preparation
• Meeting > discuss issues/defects
• Rework > corrective actions
• Follow-up > confirm finish

(repeat)

Software Testing

• Verification and validation: are we building the right software & are we building the software right
• Stress testing
• UAT
• Regression testing

Code Security Tests

Static: software is examined for common errors Dynamic: code is executed and tested (synthetic transactions)

Fuzz Testing

Dev supplied input, valid or invalid

• Generation
• Mutation (real date + changes)
• eg use Zed Attack Proxy (ZAP)

Code Repositories

Avoid dead code Public or private Sensitive info must be removed from public repositories Integrity management > check hashes

Application Management

Control: whilelist/blacklist

eg Windows AppLocker (restrict running of software)

Automated processes for updates

Host system baselining

Third-party Code

Libraries, SDKs, APIs, Outsourced code

Application Attacks

OWASP Top 10

• Injection flaws
• Broken authentication
• Sensitive data exposure
• External entities
• Broken access control
• Security misconfiguration
• XSS
• Insecure deserialization
• Using components with known vulnerability
• Insufficient logging/monitoring

Application Security

Application hardening:

• Use proper auth, encrypt data, validate user input, avoid/remediate known exploits, deploy obfuscaton and camouflage
• Prompt patching is critical
• Application config:
  • type and scope of encryption
  • access granted to authorise
  • security of underlying infrastructure

Configuration baselines allow quick identification

Prevent SQL Injection

Input validation eg never pass single quotes; use parameterised SQL

Cross-site Scripting

Takes place without knowledge of victim. Don't allow <script> in user input.

Request Forgery (CSRF/XSRF)

Uses the fact often many tabs open to different sites; auth cookies transfer between tabs. eg <img> tag but URL executes another function

• Rearchitect web app -> don't use GETs; auto-logging out users after time.

Server Side Request Forgery (SSRF)

Change metadata; being send to sever to trick

Defend Against Directory Traversal

• Webgoat and ZAP
• Prevent "." in input
• Strict access control

Overflow Attacks

When buffer size is insufficient for input data

Cookies and Attachments

Stored in browser; track activity. Used in apps too.

Session Hijacking

Cookie provides an authentication session reference. If not random -> guessable

• Cookie guessing
• Session replay attacks
• Should be sent over an encrypted channel

Code Execution Attacks

• Arbitrary code execution (perhaps remote)
• Install malicious code
• Join a botnet
• Create accounts for later use

Mitigate by:

• Limit application access
• Patch systems & applications

Privilege Escalation

Gain administrative access attacks

• Perform input validation
• Enforce least privilege principle
• Use DEP and ALSR technologies

Secure Coding Practices

Input Validation

• Whitelisting: powerful but not always possible
• Blacklisting: eg prohibit SQL keywords

Parameterized Queries

• SQL is not sent, only data to a stored procedure

Authentication and Session Management Issues

• Never store plaintext passwords: use hashed & slated (protect against rainbow attacks)
• Encrypt passwords in transit: TLS

Output Encoding

Take a dangerous character and replace, eg HTML encoding; URL encoding

Code Signing

• Obtain a cert from a CA; sign code
• Check public key to validate the signature's hash matches this code

Database Security

• Database normalisation
  • prevent inconsistency
  • prevent update anomalies
  • reduce need for restructuring
  • make DB schema more informative

1st Normal Form

• Create separate tables for different sets of related data
• Provide a primary key for every table
• Records may not have multivalued fields
• Records in a table must have the same number of fields

2nd Normal Form (adds)

• Every non-key fields must be a fact about the entire key

3rd Normal Form (adds)

• No non-key fields may be a fact about another non-key fields

Notes:

• Information at rest in a DB
• Database activity monitoring
• Use stored procedures where possible

Data Deidentification

Identifying individuals, eg ZIP/Birthday/Gender combination -> 87% unique

Anonymise data -> HIPPA standard

• Expert determination approach
• Safe harbour approach -> remove standard IDs

Data deobfuscation

• Hashing & salting
• Tokenisation: replaces sensitive fields with random identifiers
• Hashing: redact sensitive information