Harvest now, decrypt later is the strategy of stealing encrypted data today and holding it until future advances make it readable. The adversary does not need to break your encryption this year. They need your ciphertext, cheap storage, and patience.
That patience is well documented. In the Thales 2026 Quantum and AI Threat Report, 61% of security leaders named harvest-now-decrypt-later their top quantum-related concern, and industry analysis of post-quantum and AI-era attack models describes the collection as already underway, concentrated on data whose value survives for decades.
For organizations holding defense data, intellectual property, financial records, or health information, that creates an uncomfortable arithmetic: if data harvested today is decrypted in ten years, the breach effectively happened today. The exposure clock starts at collection, not at decryption. That makes decisions about data-at-rest architecture urgent in a way ordinary threat modeling does not capture.
Harvest now, decrypt later (HNDL) is an attack strategy in which adversaries collect and store encrypted data today with the expectation that future advances, most prominently a cryptographically relevant quantum computer, will make it decryptable later. The strategy has three stages: exfiltrate ciphertext through ordinary intrusion methods, archive it cheaply, and wait for the capability to mature.
Three risk vectors drive it, as the sections below examine: quantum risk to widely deployed asymmetric encryption, AI-assisted cryptanalysis that accelerates vulnerability discovery, and longevity risk, where long-retention data faces a longer exposure window than the algorithms protecting it were ever asked to survive.
Data in motion receives significant attention, but data at rest is often the long-term prize.
Adversaries focus on backup repositories, archived communications, intellectual property vaults, and high-value government or defense systems. These datasets have enduring strategic value. Even if encrypted with strong modern algorithms, attackers can exfiltrate and store them indefinitely while waiting for technological breakthroughs.
This creates three major risks:
Encryption strength alone is not sufficient. Architecture and lifecycle control matter just as much.
In a Harvest Now, Decrypt Later scenario, a single encryption layer represents a single potential future failure point. If that layer is compromised years from now, previously harvested data becomes readable.
This is why the NSA’s Commercial Solutions for Classified guidance emphasizes independently implemented dual-layered encryption for protecting classified information.
Dual-layer encryption provides:
Cigent’s approach to secure data at rest follows these layered principles, integrating multiple protection mechanisms into the storage stack itself rather than relying on a single external control. When adversaries must break two independent encryption layers instead of one, the cost, time, and computational burden increase substantially. That shift alone changes the economics of Harvest Now, Decrypt Later attacks.
The goal is not only to encrypt data. It is to make long-term decryption impractical and unattractive.
Encryption protects data while it exists. But in a Harvest Now, Decrypt Later environment, retained data becomes a long-term liability.
Old archives, decommissioned endpoints, backup images, and forgotten storage volumes are prime harvesting targets. If stolen today, they may sit in cold storage until future advances make decryption feasible.
This is where verified data sanitization becomes critical.
Rather than assuming encryption will remain unbreakable indefinitely, organizations can reduce risk by eliminating data that no longer needs to exist. Crypto-erase capabilities that destroy encryption keys, combined with block-level sanitization mechanisms embedded directly into secure storage platforms, dramatically reduce the future value of harvested ciphertext.
When encryption keys are securely destroyed, encrypted content becomes computationally infeasible to recover. When storage blocks are sanitized at the device level, residual data exposure is minimized.
To support compliance and audit requirements, Cigent also provides documented Data Erasure to verify that sanitization events have occurred as intended. This elevates erasure from a procedural claim to a verifiable control, reinforcing defensibility in regulated and classified environments.
In a post-quantum future, data that has been verifiably erased cannot be decrypted.
Two complementary mechanisms significantly reduce Harvest Now, Decrypt Later exposure:
When integrated into a CSfC-aligned architecture with independently implemented encryption layers, these mechanisms create both immediate and long-term resilience.
Together, layered encryption and verified sanitization:
Harvest Now, Decrypt Later only works if harvested data remains accessible and valuable over time. Erasure and layered encryption undermine both conditions.
Quantum breakthroughs may still be years away. AI-assisted cryptanalysis continues to evolve. But data harvesting is happening now.
Sensitive data stolen today can sit in adversary-controlled archives for decades. That timeline aligns with projected advances in quantum computing and AI-driven cryptographic research. Organizations that postpone strengthening their data at rest architecture risk creating a deferred breach scenario. The compromise occurs today, but the damage surfaces years later. In the quantum and AI era, security planning must account not only for today’s threats, but for tomorrow’s computational realities.
Harvest Now, Decrypt Later is not a theoretical problem. It is a strategic adversary model already in motion. The only question is whether the data being harvested today will still be valuable in the future. Cigent helps organizations reduce that risk through CSfC-aligned dual-layer encryption architectures, integrated secure storage, cryptographic erase capabilities, and verifiable Data Erasure.
If your organization is responsible for protecting long-retention sensitive data, classified information, intellectual property, or regulated records, now is the time to strengthen your data at rest strategy. The future of encryption resilience starts with the architecture decisions you make today.
Harvest Now, Decrypt Later (HNDL) refers to a strategy in which adversaries steal encrypted data today and store it with the expectation that future advances in quantum computing or AI-driven cryptanalysis will allow them to decrypt it later. Instead of breaking encryption immediately, attackers preserve ciphertext until technology evolves enough to make decryption feasible.
Quantum computers, once sufficiently advanced, may be capable of breaking widely used asymmetric encryption algorithms such as RSA and ECC. While large-scale cryptographically relevant quantum computers are not yet operational, progress in the field has accelerated. Because sensitive data often has long retention periods, organizations must consider whether today’s encryption will remain secure in the future.
Artificial intelligence can assist in vulnerability discovery, pattern recognition, and cryptographic research. Although AI does not magically break strong encryption, it can accelerate analysis, automate attack modeling, and reduce the cost of discovering weaknesses. Combined with future quantum advances, AI may lower the barrier to decryption over time.
Data at rest is attractive because of its long-term value. Archived emails, intellectual property, government records, financial data, and healthcare records may remain sensitive for decades. If adversaries exfiltrate encrypted backups or storage images today, they can wait years for decryption capabilities to mature. Data in motion is transient, but data at rest can be stored indefinitely.
Single-layer encryption provides strong protection today, but it creates a single potential point of future failure. If that encryption layer is broken years from now, harvested ciphertext may become readable. Layered encryption architectures, particularly those aligned with NSA Commercial Solutions for Classified guidance, introduce implementation diversity and independent cryptographic controls that make future decryption significantly more complex.
CSfC, or Commercial Solutions for Classified, is an NSA program that allows commercial products to be used in classified environments when implemented in specific layered configurations. For data at rest, CSfC requires two independent encryption layers. This reduces the risk that a single cryptographic breakthrough compromises sensitive information.
Dual-layer encryption forces an adversary to defeat two independent cryptographic implementations rather than one. Even if one algorithm or implementation is compromised in the future, the second layer remains a barrier. This increases computational cost, technical difficulty, and time, making harvested encrypted data less attractive as a long-term target.
Cryptographic erasure, also known as crypto-erase, involves securely destroying the encryption keys that protect data. Once the keys are destroyed, the encrypted data becomes computationally infeasible to recover, even if the physical storage media remains intact. This provides a fast and effective method for rendering data permanently inaccessible.
Verified block-level erasure ensures that underlying storage blocks are sanitized so that sensitive data remnants cannot be recovered. When combined with cryptographic erasure, it reduces both logical and physical recovery risks. Verification mechanisms and attestation documentation provide audit evidence that erasure has occurred as intended.
Data Erasure Attestation is documented proof that data sanitization or cryptographic erasure has been performed successfully. In regulated, defense, or high-assurance environments, attestation supports compliance, audit readiness, and defensibility. It also ensures that harvested data cannot retain long-term value because it has been verifiably destroyed.
Organizations can reduce risk by:
Post-quantum cryptography is an important part of future resilience, but it is not a complete strategy. Organizations must also address implementation diversity, key management, storage architecture, and data lifecycle control. Encryption strength, layered architecture, and verified erasure together form a more comprehensive defense against Harvest Now, Decrypt Later threats.
Harvest Now, Decrypt Later (HNDL) is a strategy in which adversaries collect encrypted data today and retain it with the expectation that future advances in quantum computing, AI-assisted cryptanalysis, or other computational capabilities may make it readable later. The data does not need to be decrypted immediately to create long-term risk.
Future cryptographically relevant quantum computers could threaten widely deployed asymmetric encryption algorithms. The concern is especially significant for information that must remain protected for years or decades because encrypted data captured today can be retained while computing capabilities advance, creating a security risk long before a sufficiently capable quantum computer exists.
AI does not automatically break strong encryption, but it can accelerate vulnerability discovery, pattern recognition, cryptographic research, and attack modeling. These capabilities can reduce the time and resources required to identify weaknesses in implementations, making AI another factor organizations should consider when evaluating the long-term durability of their data-at-rest protections.
Data at rest can retain intelligence or operational value for years. Classified information, mission data, intellectual property, archived communications, and other sensitive records can be copied and stored indefinitely after collection. That gives adversaries time to wait for advances in cryptanalysis or computing that could make previously protected information accessible.
A single encryption layer creates a single potential point of future cryptographic failure. If that algorithm or implementation is eventually compromised, previously collected ciphertext could become readable. Independently implemented encryption layers add cryptographic and implementation diversity, requiring an adversary to overcome separate protection boundaries before reaching the underlying data.
For classified data at rest, a CSfC-aligned dual-layer architecture uses two independently implemented encryption layers rather than relying on one cryptographic boundary. In Cigent’s hardware/software FDE approach, hardware full drive encryption with Pre-Boot Authentication provides one layer, while independent software full drive encryption using a different cryptographic implementation provides the second.
Dual-layer encryption requires an adversary to defeat two independent cryptographic implementations instead of one. If a future vulnerability or cryptographic development affects one layer, the second remains a separate barrier. This increases the technical difficulty, computational burden, and time required to turn harvested encrypted data into usable information.
Cryptographic erasure, or crypto erase, renders encrypted data inaccessible by securely destroying the encryption keys required to decrypt it. Rather than overwriting every stored block, the process eliminates access to the keys protecting the ciphertext, providing a rapid method for making protected information computationally infeasible to recover.
Verified block-level data erasure sanitizes storage at the block level and verifies that the intended data has been erased. Combined with cryptographic erasure, it helps reduce residual data that could otherwise remain recoverable on storage media and provides evidence that sanitization occurred as intended for audit and high-assurance environments.
Organizations can reduce HNDL exposure by identifying long-retention sensitive data, strengthening independently implemented encryption layers, minimizing unnecessary data retention, enabling cryptographic erase, performing verified block-level sanitization, and documenting erasure. They should also monitor evolving post-quantum standards and plan for cryptographic migration rather than waiting for future computing threats to mature.
Conner Crisafulli is a solutions engineer and cybersecurity professional at Cigent with a unique background bridging elite military operations and advanced data security. Before joining Cigent, Conner served six years as a U.S. Air Force Combat Controller, where he specialized in high-stakes mission planning, communication systems, and joint operations coordination/execution. Drawing from his experience in complex, contested environments, Conner now helps federal agencies and enterprise clients strengthen their data-at-rest protection strategies. At Cigent, he focuses on practical applications of self-encrypting drives (SEDs), pre-boot authentication (PBA), and various CSfC (commercial solutions for classified) technologies to safeguard sensitive data against evolving cyber threats.
