Levelling up database security by thinking in APIs

2020 saw an escalation in the volume, intensity, and tempo of cyber attacks against critical information systems. In Australia, data breaches cost $3.9m on average. Globally, ransomware cost $20B+.

One contributing factor is how we build systems to handle data about our users. No matter if you're using SQL or NoSQL — you're likely still using many of the same techniques from the advent of the web to read and write data.

The last five years have seen big leaps in how developers are designing and building APIs. What if we apply those same techniques to databases? What sort of security improvements can we unlock?

Transcript

1. Levelling up
   database security
   by thinking in APIs
   Lindsay Holmwood
   @auxesis
   Chief Product Officer @ CipherStash
   

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2. The problem
   

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3. Techniques for building secure APIs have
   improved tremendously over the last decade.
   Database security is mostly unchanged.
   

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4. Average breach costs
   $4.24m USD
   10% increase in
   average total cost of breach
   between 20202021
   

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5. The landscape is changing
   ○ Compliance requirements (e.g.,
   GDPR, CCPA are becoming
   more stringent
   ○ Ransomware cost $20B
   globally in 2020
   ○ Attackers are becoming more
   sophisticated (exploiting supply
   chains, brokering access) and
   are moving faster
   Notable breaches
   2015 Anthem Health
   80 million health records
   2020 Nintendo
   160,000 user accounts exposed
   2020 BigFooty.com
   132GB sensitive data in Elastic
   2020 Antheus Tecnologia
   81.5 million personal records
   2019 CapitalOne
   100m personal records
   

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6. In 2020, over 300,000 patient records (including detailed
   consult notes) were leaked and used to extort users.
   Vastaamo’s system violated one of the “first principles of
   cybersecurity”: It didn’t anonymize the records. It didn’t even
   encrypt them. The only thing protecting patients’ confessions and
   confidences were a couple of firewalls and a server login screen.
    Mikael Koivukangas, OneSys Medical
   Case study: Vastaamo
   

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7. The techniques
   

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8. Techniques sorted by breach
   Source: IBM Cost of a Data Breach Report 2021
   Compromised credentials
   

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9. Attackers use stolen credentials to gain access
   to a target.
   Credentials can come from:
   ● Public data breaches
   ● Version control
   ● BEC & phishing
   ● Password stores
   Compromised credentials
   Source: IBM Cost of a Data Breach report 2021
   Source: MITRE ATT&CK
   Average time to discovery:
   250 days
   

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10. Cloud misconfiguration
    Types of misconfiguration:
    ● Default
    ● Unused features
    ● Untested
    Can be used to:
    ● Expose information
    ● Gain access Source: IBM Cost of a Data Breach report 2021
    Source: OWASP Top Ten
    Average time to discovery:
    186 days
    

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11. SQL injection
    Malicious user input used in SQL queries.
    Can be used to:
    ● Exfil data
    ● Tamper with data
    ● Escalate privileges
    Average time to discovery:
    154 days
    Source: IBM Cost of a Data Breach report 2021
    Source: OWASP Top Ten
    

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12. Observer can:
    ○ view data in transit
    ○ manipulate data in
    request/response
    Person in the Middle
    Source: OWASP Top Ten
    

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13. Denial of Service
    Make the service unavailable for legitimate users
    Resource exhaustion (network, CPU, memory, storage, IO
    Can be used as cover for remote code execution and data exfil
    Source: OWASP Top Ten
    

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14. What are the big API security
    advances in the last decade?
    

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15. What can we
    learn from APIs
    and apply to databases?
    

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16. 1. Standardised
    serialisation
    formats
    

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17. Strongly typed communication for:
    ● Network transport
    ● Storage
    Reduces attack surface, to mitigate attacks like
    ● SQL injection
    Serialisation formats
    

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18. Example: Protocol Buffers
    Binary representation of data
    structures:
    1. Describe data structure using
    built in types
    2. Compile bindings for languages
    3. Encode/decode data structure in
    efficient binary format
    Supports basic backwards
    compatibility via tags.
    service SearchService {
    rpc Search(SearchRequest) returns (SearchResponse);
    }
    message SearchRequest {
    required string query = 1;
    optional int32 page_number = 2;
    optional int32 result_per_page = 3;
    }
    message SearchResponse {
    repeated Result results = 1;
    }
    message Result {
    string url = 1;
    string title = 2;
    repeated string snippets = 3;
    }
    

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19. Example: BSON
    Lightweight binary representation of
    data structures.
    Binary encoding of JSON-like data
    (includes field names in encoded
    data).
    Handle marshal/unmarshal in each
    language.
    {"hello": "world"} →
    \x16\x00\x00\x00 // total document size
    \x02 // 0x02 = type String
    hello\x00 // field name
    \x06\x00\x00\x00world\x00 // field value
    \x00 // 0x00 = type EOO
    

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20. For databases?
    

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21. Build secure clients, faster:
    ● Automatically generate clients for different languages
    ● Automatically generate documentation
    ● Backwards compatibility baked in
    Serialisation formats for databases
    

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22. Deserialization attacks:
    ● Injection — data injection, only support primitive data types
    ● Privilege escalation — gaining RCE through object deserialisation
    Denial of Service attacks:
    ● Resource exhaustion — drop and log bad deserialisations
    Serialisation formats — defend against:
    

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23. Defence in depth:
    ● Use strongly typed languages to stop injection attacks
    propagating from client to server
    “New” attacks like request smuggling
    Serialisation formats — but also consider:
    

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24. 2. RPC
    

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25. RPC  before
    Single Request/Response APIs:
    ● CORBA
    ● SOAP HTTP, XML
    ● XMLRPC
    ● REST HTTP, URI, JSON, XML
    Databases:
    ● Unique wire protocols
    

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26. Use code generation to handle:
    ● Routes
    ● Serialisation
    ● HTTP methods, request/response headers
    ● Errors
    RPC  now
    

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27. Example: gRPC
    From Google
    Uses protobufs
    Requires HTTP/2
    Bidirectional streaming
    

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28. Example: Twirp
    From Twitch
    Supports binary and JSON payloads
    HTTP 1.1 only
    No bidirectional streaming
    

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29. Example: GraphQL
    “Query language for APIs”
    Single API endpoint.
    Clients request the data and the
    structure.
    New fields and types can be added
    without affecting existing queries.
    Query:
    {
    person {
    name
    height
    }
    }
    Response:
    {
    “person”: {
    “name”: “Ada Lovelace”,
    “height”: 166
    }
    }
    

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30. For databases?
    

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31. RPC for databases
    Ensure protocol compatibility between client and server
    ● Force clients to upgrade to latest versions
    Reduce attack surface
    ● To only what the endpoint explicitly exposes
    ● Stop enumeration
    

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32. Broken authentication
    ● Session timeouts to limit foothold, through short lived tokens
    Broken access controls
    ● Privilege escalation, through scoped credentials
    Denial of service
    ● Strict encoding and deserialization
    ● Logging of deserialization failures
    RPC  defend against:
    

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33. gRPC reflection
    ● Enumerates gRPC services
    ● Exposes protobufs in human readable format (arguments, fields)
    You can use this now!
    ● ProfaneDB defines schema in protobufs and talks gRPC
    RPC  but also consider:
    

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34. 3. Auth
    

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35. Auth — before
    Authentication:
    ● Challenge–Response authentication
    ● Secure Remote Password protocol
    ● Client certificate authentication
    

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36. Auth — now
    Authentication:
    ● OAuth2  JWT
    ● SAML
    ● Self managed identity via G Suite, O365
    Proliferation of third party IDP
    ● Auth0
    ● Ping
    ● Okta
    

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37. For databases?
    

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38. Auth for databases
    Don’t roll your own auth — use third party identity provider
    Untrusted clients, trusted servers:
    ● Client authenticates to IDP
    ● IDP sets up session with database
    ● Database is ignorant of users — only knows if IDP gives an OK
    

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39. Auth for databases
    Benefits:
    ● Less code, lower ongoing costs
    ● Database is integrated with broader organisational IAM controls
    You can use this now!
    ● MongoDB, OpenSearch, CouchDB all support JWT authentication
    

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40. Auth — defend against:
    Broken authentication
    ● Limit impact of compromised credentials and account takeovers
    ⬆ involved in 20% of all breaches
    Broken access controls
    ● Privilege escalation, through strictly scoped credentials
    

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41. 4. TLS everywhere
    

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42. Certs were costly!
    Economise by not using TLS everywhere:
    ● TLS termination at your load balancers
    ● Unencrypted from load balancers onwards
    Poor automation for managing cert lifecycle
    Poor visibility into certificate supply chain
    TLS  before
    

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43. Certificates are basically free
    Proliferation of end-to-end TLS
    Better developer experience for the entire lifecycle:
    ○ Let’s Encrypt — automates nearly the entire cert lifecycle
    ○ mkcert — can use certs in local dev
    Certificate Transparency logs create supply chain visibility
    TLS  now
    

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44. For databases?
    

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45. TLS for databases
    Terminate TLS in the database server itself
    Handle the cert lifecycle in the database server itself
    Use well-automated PKI infrastructure
    Strictly use Forward Secrecy ciphers (ECDHE, DHE
    

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46. Sensitive data exposure:
    ● Observer can view data in transit (PITM
    Injection attacks:
    ● Attacker can inject data into request/response (PITM
    Replay attacks (with TLS 1.2
    ● Attacker can perform operations repeatedly
    Impersonation:
    ● Monitor cert transparency logs for compromised CAs
    TLS  defend against:
    

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47. $ subfinder -silent -d cipherstash.com
    discuss.cipherstash.com
    landing.cipherstash.com
    docs.cipherstash.com
    dev.cipherstash.com
    Easier passive asset discovery:
    ● Cert transparency logs fasttrack some asset discovery
    TLS  but also consider:
    

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48. Zero trust
    

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49. “never trust, always verify”
    Build all your systems like they are connected to the public internet
    All input is untrusted — sanitise everything
    Expose database to the network?
    

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50. Thank you!
    🙋 What questions do you have?
    💖 the talk? Let @auxesis know.
    

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51. Appendix: Data Serialization Formats
    ● Protocol Buffers [developers.google.com]
    ● BSON [bsonspec.org]
    ● Apache Avro [arvo.apache.org]
    

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52. Appendix: JWT-based database authentication
    ● Custom JWT Authentication [docs.mongodb.com]
    ● Use JSON Web Tokens (JWTs) to Authenticate in Open Distro for
    Elasticsearch and Kibana [aws.amazon.com]
    ● Authentication — Apache CouchDB [docs.couchdb.org]
    

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53. Appendix: Attack Techniques
    ● HTTP Request Smuggling [portswigger.net]
    ● Credential Access techniques [attack.mitre.org]
    

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54. Other security advances I didn’t have time to cover
    ● Web Application Firewalls
    ● Infracode static analysis
    ○ Semgrep
    ● Reproducible builds
    ○ Bazel
    

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