This paper presents the first adaptively secure streaming functional encryption (sFE) scheme for \(\mathsf {P/Poly}\) . sFE extends traditional FE to vast and/or dynamically evolving data sets, enabling incremental encryption of streaming inputs and iterative partial decryption over encrypted prefixes. The proposed sFE scheme is built from indistinguishability obfuscation for \(\mathsf {P/Poly}\) and injective PRGs. We achieve this result via two core technical contributions which may be of independent interest. First, we introduce a novel “gluing” mechanism to achieve adaptive security by intertwining two schemes, each possessing one aspect of adaptive security. Second, we enhance the powerful Koppula-Lewko-Waters [STOC 2015] framework with a “sliding window” technique, enabling authenticated iterative computation with fresh inputs at each iteration. Prior work by Guan, Korb, and Sahai [CRYPTO 2023] constructed sFE but only under a (semi-adaptive) function-selective security model, requiring all functional keys to be queried before observing any ciphertext. This severe limitation precludes practical scenarios and leaves adaptive security as a crucial open challenge – explicitly highlighted by their work—which we address in this paper.