Serverless Validator for Payload Injection Security
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Solution Overview
Problem
Serverless computing architectures are vulnerable to malicious payload injection and source code modification, as messaging queues can be misconfigured or inadequately protected, allowing unauthorized access and processing of untrusted data.
Innovation Solution
Implementing a validator system that generates and verifies a validation value based on the payload and source code, ensuring that only trusted payloads are processed by comparing computed and received values, using hash or encrypted data to authenticate the source of the payload before execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If messaging queues are misconfigured or inadequately protected to enable serverless computing, then ease of operation and automation are improved, but security and reliability deteriorate due to vulnerability to malicious payload injection
Solution Approach 1:
The validator computes and attaches a validation value (hash) to the payload before the payload is processed by subsequent functions. This preliminary validation mechanism is embedded in the function execution flow, automatically verifying payload integrity without requiring manual configuration or intervention, thus maintaining ease of operation while preventing malicious injection.
Solution Approach 2:
The validator acts as an intermediary component between function execution and payload processing. It intercepts payloads, computes validation values, and verifies integrity before allowing execution to proceed. This intermediary layer provides security without requiring changes to the underlying messaging queue configuration, preserving ease of operation while eliminating security vulnerabilities.
2Reliability
If validation mechanisms are implemented to verify payload source, then security and reliability are improved, but device complexity increases due to additional validation steps
Solution Approach 1:
The validator is implemented as a self-service component that automatically computes validation values using the function's source code and payload, then verifies these values without requiring external validation infrastructure. The validator retrieves source code, computes hashes, and performs verification autonomously within the function execution environment, adding security without proportionally increasing system complexity.
Solution Approach 2:
The validation functionality is merged into the existing function execution pipeline. The validator computes validation values using the same source code that defines the function logic, combining verification operations with execution operations. This merging approach adds security while minimizing additional complexity by reusing existing components and data structures.
3Reliability
If validation values are computed and verified for each payload, then reliability against malicious injection is improved, but productivity decreases due to additional computation overhead
Solution Approach 1:
The validation mechanism uses hash computation with predetermined algorithms that optimize the balance between security and performance. By selecting appropriate hash functions and computing parameters, the system achieves reliable validation while minimizing computation overhead. The validation value computation is performed efficiently using the function's source code as input, reducing the impact on processing speed.
Data Source
AI summary
A serverless computing framework is secured against malicious payload injection. A series of functions can be strung together to perform a workflow in response to a triggering event. A validator can be included with a function that verifies that an input payload originated from a trusted source. A validation value, such as a hash, can be computed based on the result payload in combination with the source code of the function that produced the result payload. A downstream function can receive the result payload and the hash and utilize the result payload and a copy of the upstream source code to produce another hash. The received and generated hashes can then be compared and utilized to control execution of the downstream function. Execution can be prevented when there is a mismatch between the hashes.