Attackers use deserialization functions to turn crafted input into objects or data structures that trigger unsafe behaviour. If the function accepts untrusted data without strict type and integrity checks, it can lead to code execution, logic abuse or privilege misuse. Restrict accepted formats, verify integrity, and never deserialize untrusted data without controls.
How attackers turn deserialization into an execution path
Deserialization is not just a format conversion step. In insecure implementations, it becomes a trust boundary where crafted input can reconstitute attacker-chosen object graphs, invoke dangerous methods, or alter control flow before the application has validated the data. The risk is highest when the code accepts untrusted input, allows complex object types, or relies on side effects during object construction or hydration.
In practice, attackers look for functions that accept serialized blobs from cookies, APIs, message queues, files, or inter-service calls and then assume the data is safe. If the deserializer can instantiate unexpected classes or trigger gadget chains, the payload can move from parsing to execution without the application ever explicitly calling the risky code path.
What attackers are trying to achieve with crafted serialized input
The first goal is often code execution, but deserialization abuse is broader than that. A successful payload may change business logic, bypass authorisation checks, create or overwrite privileged objects, or poison in-memory state so later requests behave unsafely. In some systems, the payload does not need to execute a shell command to be useful, it only needs to alter the object state in a way the application later trusts.
Attackers also use deserialization to find hidden capabilities in libraries and frameworks. If the application loads classes automatically, accepts polymorphic types, or chains object methods during reconstruction, the attacker may be able to reach functionality that was never intended to be exposed through the original request path.
Why deserialization functions become dangerous when they trust input
The core weakness is trust. A deserialization function that assumes the payload is authentic, well-formed, and compatible with the expected type system can become an execution primitive. When type checks are weak, integrity is not verified, or unsafe object hooks are enabled, the application may process a malicious structure as if it came from a trusted producer.
This is why deserialization issues often overlap with gadget-chain abuse, object injection, and unsafe polymorphism. The danger is not the conversion itself, but the hidden behaviours attached to object restoration. The Insecure Deserialisation Guide covers the attack patterns that turn ordinary parsing into a high-impact exploit path.
Risk and Threat Considerations
Deserialization flaws are attractive because they often sit behind a normal application feature, not an obviously exposed admin function. Attackers can hide malicious payloads inside routine traffic, then rely on object reconstruction, gadget chains, or follow-on logic to gain execution, persistence, or privilege misuse.
Failure mechanism: The application reconstructs attacker-controlled data into live objects before validating type, origin, or integrity, allowing unsafe methods or chained behaviours to run in-process.
Impact: The result can be remote code execution, logic abuse, account or privilege misuse, or a deeper compromise if the process has access to secrets, internal services, or privileged runtime context.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
MITRE ATT&CK addresses the attack and risk surface, while OWASP ASVS, NIST SP 800-53 Rev 5 and CIS Controls v8 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| MITRE ATT&CK | T1055 — Process Injection | Deserialization abuse can yield code execution or process compromise. |
| Recommendation — Map deserialization exploit paths to execution and hunt for post-exploitation behaviour. | ||
| OWASP ASVS | V1 — Encoding and Sanitization | Unsafe parsing and object reconstruction depend on input handling weaknesses. |
| Recommendation — Validate and constrain input before it reaches deserialization logic. | ||
| NIST SP 800-53 Rev 5 | SI-10 — Information Input Validation | Deserialization attacks exploit insufficient validation of untrusted input. |
| IA-5 — Authenticator Management | Malicious deserialization may expose or misuse credentials, sessions, or tokens. | |
| Recommendation — Apply strict input validation before accepting serialized data. Rotate any exposed secrets or tokens after a suspected deserialization compromise. | ||
| CIS Controls v8 | CIS-16 — Application Software Security | Secure coding controls are needed to prevent unsafe deserialization paths. |
| Recommendation — Review application code for unsafe deserialization and replace it with safer parsing. | ||
Practitioner Guidance
What to verify: Confirm exactly which inputs reach deserialization, which types are accepted, and whether the parser can instantiate unexpected classes or invoke custom callbacks. Treat any path that accepts unauthenticated or user-controlled serialized data as high risk until proven otherwise.
Decision rule: If the function must process external data, prefer a safer data format and enforce a strict allowlist of expected schemas and types. If that is not possible, require integrity protection, disable dangerous object features, and test for gadget-chain behaviour rather than only checking whether the payload parses.
Practitioner takeaway: The important control decision is not “can we deserialize this?”, it is “can we prove the payload is trusted and the resulting object cannot trigger unintended behaviour?”
Related resources from NHI Mgmt Group
- Guide: Web Application Attacks Guide
- How do attackers turn a supply-chain incident into wider NHI compromise?
- How do attackers operationalise stolen OAuth tokens at scale?
- Why do attackers often check model availability before trying to generate content?
- How do attackers turn stolen npm secrets into broader compromise?