开发能力指攻击者自主构建恶意工具和基础设施的过程，涵盖恶意软件开发、漏洞利用构造、伪造证书创建等环节。与传统武器采购不同，自主开发可避免商业恶意软件的特征暴露，并实现攻击工具的高度定制化。防御方面主要通过逆向工程分析代码特征、追踪数字证书指纹、监控可疑编译行为等手段进行检测，重点关注恶意软件与已知攻击组织的代码相似性、证书签发异常等特征。
为规避开发环节的特征暴露风险，攻击者采用模块化解耦、供应链污染、虚拟化隔离等策略重构开发流程，将恶意代码生产嵌入合法软件开发体系，并通过技术手段消除开发环境特征。这些匿迹技术使得攻击工具的研发、测试、部署全过程呈现高度隐蔽性，显著提升防御方溯源取证的难度。
当前开发能力匿迹技术的核心在于构建"合法化"开发链路与实施"去特征化"生产流程。攻击者通过技术融合与流程再造，将恶意代码开发行为解构并隐匿于多个合法维度：模块化架构将恶意功能拆分为无害组件，在动态加载环节重组攻击能力；工具链污染利用开源生态的信任传递机制，将攻击代码植入合法软件的生产源头；自签证书体系仿造数字信任基础设施，为恶意代码赋予表面合法性；虚拟化环境则通过技术隔离消除开发痕迹。这些技术的共性在于突破传统单点对抗模式，将攻击能力开发过程深度嵌入IT产业标准流程，利用软件供应链的复杂性稀释恶意特征，使得防御方难以通过局部检测发现完整攻击链条。
| 效应类型 | 是否存在 |
|---|---|
| 特征伪装 | ✅ |
| 行为透明 | ✅ |
| 数据遮蔽 | ✅ |
| 时空释痕 | ✅ |
攻击者通过仿造合法软件开发流程和数字证书体系，将恶意代码生产行为伪装成正常软件工程活动。例如使用企业级代码签名证书为恶意软件背书，或篡改开源工具链使其输出携带隐蔽恶意功能的合法软件，使得开发产物在表面特征层面与合规软件无异。
采用虚拟化开发环境和自动化构建流水线，使恶意代码开发过程完全脱离物理设备特征。攻击者利用云服务的资源池化特性，使得开发行为无法关联到特定实体设备或地理位置，传统基于设备指纹的溯源机制失效。
在开发全链路实施加密保护，包括代码存储加密、通信信道加密、编译产物加密传输等。私有证书体系的加密通信掩盖了恶意代码的传输细节，内存驻留开发模式避免磁盘数据残留，关键开发数据仅以密文形态存在于临时性存储介质。
通过全球化云资源调度和分布式协作开发，将开发任务拆解至不同司法管辖区的临时性节点执行。攻击者利用云服务的弹性扩展特性，使开发环境的创建、使用、销毁周期短于多数取证系统的响应阈值，将攻击特征稀释在持续变动的云资源池中。
| ID | Name | Description |
|---|---|---|
| G0094 | Kimsuky |
Kimsuky created and used a mailing toolkit to use in spearphishing attacks.[1] |
| G1036 | Moonstone Sleet |
Moonstone Sleet developed malicious npm packages for delivery to or retrieval by victims.[2] |
| ID | Mitigation | Description |
|---|---|---|
| M1056 | Pre-compromise |
This technique cannot be easily mitigated with preventive controls since it is based on behaviors performed outside of the scope of enterprise defenses and controls. |
| ID | Data Source | Data Component | Detects |
|---|---|---|---|
| DS0035 | Internet Scan | Response Content |
Consider use of services that may aid in the tracking of capabilities, such as certificates, in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of information to uncover other adversary infrastructure.[3] Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control. |
| DS0004 | Malware Repository | Malware Content |
Consider analyzing malware for features that may be associated with the adversary and/or their developers, such as compiler used, debugging artifacts, or code similarities. Malware repositories can also be used to identify additional samples associated with the adversary and identify development patterns over time. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control. |
| Malware Metadata |
Monitor for contextual data about a malicious payload, such as compilation times, file hashes, as well as watermarks or other identifiable configuration information. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control. |